flann: apply CV_OVERRIDE/CV_FINAL

modules/flann/include/opencv2/flann/any.h

@@ -54,50 +54,50 @@ struct base_any_policy
 template<typename T>
 struct typed_base_any_policy : base_any_policy
 {
-    virtual ::size_t get_size() { return sizeof(T); }
-    virtual const std::type_info& type() { return typeid(T); }
+    virtual ::size_t get_size() CV_OVERRIDE { return sizeof(T); }
+    virtual const std::type_info& type() CV_OVERRIDE { return typeid(T); }
 
 };
 
 template<typename T>
-struct small_any_policy : typed_base_any_policy<T>
+struct small_any_policy CV_FINAL : typed_base_any_policy<T>
 {
-    virtual void static_delete(void**) { }
-    virtual void copy_from_value(void const* src, void** dest)
+    virtual void static_delete(void**) CV_OVERRIDE { }
+    virtual void copy_from_value(void const* src, void** dest) CV_OVERRIDE
     {
         new (dest) T(* reinterpret_cast<T const*>(src));
     }
-    virtual void clone(void* const* src, void** dest) { *dest = *src; }
-    virtual void move(void* const* src, void** dest) { *dest = *src; }
-    virtual void* get_value(void** src) { return reinterpret_cast<void*>(src); }
-    virtual const void* get_value(void* const * src) { return reinterpret_cast<const void*>(src); }
-    virtual void print(std::ostream& out, void* const* src) { out << *reinterpret_cast<T const*>(src); }
+    virtual void clone(void* const* src, void** dest) CV_OVERRIDE { *dest = *src; }
+    virtual void move(void* const* src, void** dest) CV_OVERRIDE { *dest = *src; }
+    virtual void* get_value(void** src) CV_OVERRIDE { return reinterpret_cast<void*>(src); }
+    virtual const void* get_value(void* const * src) CV_OVERRIDE { return reinterpret_cast<const void*>(src); }
+    virtual void print(std::ostream& out, void* const* src) CV_OVERRIDE { out << *reinterpret_cast<T const*>(src); }
 };
 
 template<typename T>
-struct big_any_policy : typed_base_any_policy<T>
+struct big_any_policy CV_FINAL : typed_base_any_policy<T>
 {
-    virtual void static_delete(void** x)
+    virtual void static_delete(void** x) CV_OVERRIDE
     {
         if (* x) delete (* reinterpret_cast<T**>(x));
         *x = NULL;
     }
-    virtual void copy_from_value(void const* src, void** dest)
+    virtual void copy_from_value(void const* src, void** dest) CV_OVERRIDE
     {
         *dest = new T(*reinterpret_cast<T const*>(src));
     }
-    virtual void clone(void* const* src, void** dest)
+    virtual void clone(void* const* src, void** dest) CV_OVERRIDE
     {
         *dest = new T(**reinterpret_cast<T* const*>(src));
     }
-    virtual void move(void* const* src, void** dest)
+    virtual void move(void* const* src, void** dest) CV_OVERRIDE
     {
         (*reinterpret_cast<T**>(dest))->~T();
         **reinterpret_cast<T**>(dest) = **reinterpret_cast<T* const*>(src);
     }
-    virtual void* get_value(void** src) { return *src; }
-    virtual const void* get_value(void* const * src) { return *src; }
-    virtual void print(std::ostream& out, void* const* src) { out << *reinterpret_cast<T const*>(*src); }
+    virtual void* get_value(void** src) CV_OVERRIDE { return *src; }
+    virtual const void* get_value(void* const * src) CV_OVERRIDE { return *src; }
+    virtual void print(std::ostream& out, void* const* src) CV_OVERRIDE { out << *reinterpret_cast<T const*>(*src); }
 };
 
 template<> inline void big_any_policy<flann_centers_init_t>::print(std::ostream& out, void* const* src)

modules/flann/include/opencv2/flann/autotuned_index.h

@@ -100,7 +100,7 @@ public:
     /**
      *          Method responsible with building the index.
      */
-    virtual void buildIndex()
+    virtual void buildIndex() CV_OVERRIDE
     {
         std::ostringstream stream;
         bestParams_ = estimateBuildParams();
@@ -124,7 +124,7 @@ public:
     /**
      *  Saves the index to a stream
      */
-    virtual void saveIndex(FILE* stream)
+    virtual void saveIndex(FILE* stream) CV_OVERRIDE
     {
         save_value(stream, (int)bestIndex_->getType());
         bestIndex_->saveIndex(stream);
@@ -134,7 +134,7 @@ public:
     /**
      *  Loads the index from a stream
      */
-    virtual void loadIndex(FILE* stream)
+    virtual void loadIndex(FILE* stream) CV_OVERRIDE
     {
         int index_type;
 
@@ -151,7 +151,7 @@ public:
     /**
      *      Method that searches for nearest-neighbors
      */
-    virtual void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    virtual void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
         int checks = get_param<int>(searchParams,"checks",FLANN_CHECKS_AUTOTUNED);
         if (checks == FLANN_CHECKS_AUTOTUNED) {
@@ -163,7 +163,7 @@ public:
     }
 
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return bestIndex_->getParameters();
     }
@@ -182,7 +182,7 @@ public:
     /**
      *      Number of features in this index.
      */
-    virtual size_t size() const
+    virtual size_t size() const CV_OVERRIDE
     {
         return bestIndex_->size();
     }
@@ -190,7 +190,7 @@ public:
     /**
      *  The length of each vector in this index.
      */
-    virtual size_t veclen() const
+    virtual size_t veclen() const CV_OVERRIDE
     {
         return bestIndex_->veclen();
     }
@@ -198,7 +198,7 @@ public:
     /**
      * The amount of memory (in bytes) this index uses.
      */
-    virtual int usedMemory() const
+    virtual int usedMemory() const CV_OVERRIDE
     {
         return bestIndex_->usedMemory();
     }
@@ -206,7 +206,7 @@ public:
     /**
      * Algorithm name
      */
-    virtual flann_algorithm_t getType() const
+    virtual flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_AUTOTUNED;
     }

modules/flann/include/opencv2/flann/composite_index.h

@@ -101,7 +101,7 @@ public:
     /**
      * @return The index type
      */
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_COMPOSITE;
     }
@@ -109,7 +109,7 @@ public:
     /**
      * @return Size of the index
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return kdtree_index_->size();
     }
@@ -117,7 +117,7 @@ public:
     /**
      * \returns The dimensionality of the features in this index.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return kdtree_index_->veclen();
     }
@@ -125,7 +125,7 @@ public:
     /**
      * \returns The amount of memory (in bytes) used by the index.
      */
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return kmeans_index_->usedMemory() + kdtree_index_->usedMemory();
     }
@@ -133,7 +133,7 @@ public:
     /**
      * \brief Builds the index
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         Logger::info("Building kmeans tree...\n");
         kmeans_index_->buildIndex();
@@ -145,7 +145,7 @@ public:
      * \brief Saves the index to a stream
      * \param stream The stream to save the index to
      */
-    void saveIndex(FILE* stream)
+    void saveIndex(FILE* stream) CV_OVERRIDE
     {
         kmeans_index_->saveIndex(stream);
         kdtree_index_->saveIndex(stream);
@@ -155,7 +155,7 @@ public:
      * \brief Loads the index from a stream
      * \param stream The stream from which the index is loaded
      */
-    void loadIndex(FILE* stream)
+    void loadIndex(FILE* stream) CV_OVERRIDE
     {
         kmeans_index_->loadIndex(stream);
         kdtree_index_->loadIndex(stream);
@@ -164,7 +164,7 @@ public:
     /**
      * \returns The index parameters
      */
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return index_params_;
     }
@@ -172,7 +172,7 @@ public:
     /**
      * \brief Method that searches for nearest-neighbours
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
         kmeans_index_->findNeighbors(result, vec, searchParams);
         kdtree_index_->findNeighbors(result, vec, searchParams);

modules/flann/include/opencv2/flann/flann_base.hpp

@@ -128,7 +128,7 @@ public:
     /**
      * Builds the index.
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         if (!loaded_) {
             nnIndex_->buildIndex();
@@ -150,7 +150,7 @@ public:
      * \brief Saves the index to a stream
      * \param stream The stream to save the index to
      */
-    virtual void saveIndex(FILE* stream)
+    virtual void saveIndex(FILE* stream) CV_OVERRIDE
     {
         nnIndex_->saveIndex(stream);
     }
@@ -159,7 +159,7 @@ public:
      * \brief Loads the index from a stream
      * \param stream The stream from which the index is loaded
      */
-    virtual void loadIndex(FILE* stream)
+    virtual void loadIndex(FILE* stream) CV_OVERRIDE
     {
         nnIndex_->loadIndex(stream);
     }
@@ -167,7 +167,7 @@ public:
     /**
      * \returns number of features in this index.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return nnIndex_->veclen();
     }
@@ -175,7 +175,7 @@ public:
     /**
      * \returns The dimensionality of the features in this index.
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return nnIndex_->size();
     }
@@ -183,7 +183,7 @@ public:
     /**
      * \returns The index type (kdtree, kmeans,...)
      */
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return nnIndex_->getType();
     }
@@ -191,7 +191,7 @@ public:
     /**
      * \returns The amount of memory (in bytes) used by the index.
      */
-    virtual int usedMemory() const
+    virtual int usedMemory() const CV_OVERRIDE
     {
         return nnIndex_->usedMemory();
     }
@@ -200,7 +200,7 @@ public:
     /**
      * \returns The index parameters
      */
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return nnIndex_->getParameters();
     }
@@ -213,7 +213,7 @@ public:
      * \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)
+    void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params) CV_OVERRIDE
     {
         nnIndex_->knnSearch(queries, indices, dists, knn, params);
     }
@@ -227,7 +227,7 @@ public:
      * \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)
+    int radiusSearch(const Matrix<ElementType>& query, Matrix<int>& indices, Matrix<DistanceType>& dists, float radius, const SearchParams& params) CV_OVERRIDE
     {
         return nnIndex_->radiusSearch(query, indices, dists, radius, params);
     }
@@ -235,7 +235,7 @@ public:
     /**
      * \brief Method that searches for nearest-neighbours
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
         nnIndex_->findNeighbors(result, vec, searchParams);
     }

modules/flann/include/opencv2/flann/hierarchical_clustering_index.h

@@ -435,7 +435,7 @@ public:
     /**
      *  Returns size of index.
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return size_;
     }
@@ -443,7 +443,7 @@ public:
     /**
      * Returns the length of an index feature.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return veclen_;
     }
@@ -453,7 +453,7 @@ public:
      * Computes the inde memory usage
      * Returns: memory used by the index
      */
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return pool.usedMemory+pool.wastedMemory+memoryCounter;
     }
@@ -461,7 +461,7 @@ public:
     /**
      * Builds the index
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         if (branching_<2) {
             throw FLANNException("Branching factor must be at least 2");
@@ -480,13 +480,13 @@ public:
     }
 
 
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_HIERARCHICAL;
     }
 
 
-    void saveIndex(FILE* stream)
+    void saveIndex(FILE* stream) CV_OVERRIDE
     {
         save_value(stream, branching_);
         save_value(stream, trees_);
@@ -501,7 +501,7 @@ public:
     }
 
 
-    void loadIndex(FILE* stream)
+    void loadIndex(FILE* stream) CV_OVERRIDE
     {
         free_elements();
 
@@ -544,7 +544,7 @@ public:
      *     vec = the vector for which to search the nearest neighbors
      *     searchParams = parameters that influence the search algorithm (checks)
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
 
         int maxChecks = get_param(searchParams,"checks",32);
@@ -569,7 +569,7 @@ public:
 
     }
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return params;
     }

modules/flann/include/opencv2/flann/kdtree_index.h

@@ -120,7 +120,7 @@ public:
     /**
      * Builds the index
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         /* Construct the randomized trees. */
         for (int i = 0; i < trees_; i++) {
@@ -136,13 +136,13 @@ public:
     }
 
 
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_KDTREE;
     }
 
 
-    void saveIndex(FILE* stream)
+    void saveIndex(FILE* stream) CV_OVERRIDE
     {
         save_value(stream, trees_);
         for (int i=0; i<trees_; ++i) {
@@ -152,7 +152,7 @@ public:
 
 
 
-    void loadIndex(FILE* stream)
+    void loadIndex(FILE* stream) CV_OVERRIDE
     {
         load_value(stream, trees_);
         if (tree_roots_!=NULL) {
@@ -170,7 +170,7 @@ public:
     /**
      *  Returns size of index.
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return size_;
     }
@@ -178,7 +178,7 @@ public:
     /**
      * Returns the length of an index feature.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return veclen_;
     }
@@ -187,7 +187,7 @@ public:
      * Computes the inde memory usage
      * Returns: memory used by the index
      */
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return int(pool_.usedMemory+pool_.wastedMemory+dataset_.rows*sizeof(int));  // pool memory and vind array memory
     }
@@ -201,7 +201,7 @@ public:
      *     vec = the vector for which to search the nearest neighbors
      *     maxCheck = the maximum number of restarts (in a best-bin-first manner)
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
         int maxChecks = get_param(searchParams,"checks", 32);
         float epsError = 1+get_param(searchParams,"eps",0.0f);
@@ -214,7 +214,7 @@ public:
         }
     }
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return index_params_;
     }

modules/flann/include/opencv2/flann/kdtree_single_index.h

@@ -114,7 +114,7 @@ public:
     /**
      * Builds the index
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         computeBoundingBox(root_bbox_);
         root_node_ = divideTree(0, (int)size_, root_bbox_ );   // construct the tree
@@ -133,13 +133,13 @@ public:
         }
     }
 
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_KDTREE_SINGLE;
     }
 
 
-    void saveIndex(FILE* stream)
+    void saveIndex(FILE* stream) CV_OVERRIDE
     {
         save_value(stream, size_);
         save_value(stream, dim_);
@@ -154,7 +154,7 @@ public:
     }
 
 
-    void loadIndex(FILE* stream)
+    void loadIndex(FILE* stream) CV_OVERRIDE
     {
         load_value(stream, size_);
         load_value(stream, dim_);
@@ -179,7 +179,7 @@ public:
     /**
      *  Returns size of index.
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return size_;
     }
@@ -187,7 +187,7 @@ public:
     /**
      * Returns the length of an index feature.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return dim_;
     }
@@ -196,7 +196,7 @@ public:
      * Computes the inde memory usage
      * Returns: memory used by the index
      */
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return (int)(pool_.usedMemory+pool_.wastedMemory+dataset_.rows*sizeof(int));  // pool memory and vind array memory
     }
@@ -210,7 +210,7 @@ public:
      * \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)
+    void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params) CV_OVERRIDE
     {
         assert(queries.cols == veclen());
         assert(indices.rows >= queries.rows);
@@ -225,7 +225,7 @@ public:
         }
     }
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return index_params_;
     }
@@ -239,7 +239,7 @@ public:
      *     vec = the vector for which to search the nearest neighbors
      *     maxCheck = the maximum number of restarts (in a best-bin-first manner)
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
         float epsError = 1+get_param(searchParams,"eps",0.0f);
 

modules/flann/include/opencv2/flann/kmeans_index.h

@@ -266,7 +266,7 @@ public:
 
 public:
 
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_KMEANS;
     }
@@ -291,7 +291,7 @@ public:
         {
         }
 
-        void operator()(const cv::Range& range) const
+        void operator()(const cv::Range& range) const CV_OVERRIDE
         {
             const int begin = range.start;
             const int end = range.end;
@@ -398,7 +398,7 @@ public:
     /**
      *  Returns size of index.
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return size_;
     }
@@ -406,7 +406,7 @@ public:
     /**
      * Returns the length of an index feature.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return veclen_;
     }
@@ -421,7 +421,7 @@ public:
      * Computes the inde memory usage
      * Returns: memory used by the index
      */
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return pool_.usedMemory+pool_.wastedMemory+memoryCounter_;
     }
@@ -429,7 +429,7 @@ public:
     /**
      * Builds the index
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         if (branching_<2) {
             throw FLANNException("Branching factor must be at least 2");
@@ -448,7 +448,7 @@ public:
     }
 
 
-    void saveIndex(FILE* stream)
+    void saveIndex(FILE* stream) CV_OVERRIDE
     {
         save_value(stream, branching_);
         save_value(stream, iterations_);
@@ -460,7 +460,7 @@ public:
     }
 
 
-    void loadIndex(FILE* stream)
+    void loadIndex(FILE* stream) CV_OVERRIDE
     {
         load_value(stream, branching_);
         load_value(stream, iterations_);
@@ -495,7 +495,7 @@ public:
      *     vec = the vector for which to search the nearest neighbors
      *     searchParams = parameters that influence the search algorithm (checks, cb_index)
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
     {
 
         int maxChecks = get_param(searchParams,"checks",32);
@@ -554,7 +554,7 @@ public:
         return clusterCount;
     }
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return index_params_;
     }

modules/flann/include/opencv2/flann/linear_index.h

@@ -63,47 +63,47 @@ public:
     LinearIndex(const LinearIndex&);
     LinearIndex& operator=(const LinearIndex&);
 
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_LINEAR;
     }
 
 
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return dataset_.rows;
     }
 
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return dataset_.cols;
     }
 
 
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return 0;
     }
 
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         /* nothing to do here for linear search */
     }
 
-    void saveIndex(FILE*)
+    void saveIndex(FILE*) CV_OVERRIDE
     {
         /* nothing to do here for linear search */
     }
 
 
-    void loadIndex(FILE*)
+    void loadIndex(FILE*) CV_OVERRIDE
     {
         /* nothing to do here for linear search */
 
         index_params_["algorithm"] = getType();
     }
 
-    void findNeighbors(ResultSet<DistanceType>& resultSet, const ElementType* vec, const SearchParams& /*searchParams*/)
+    void findNeighbors(ResultSet<DistanceType>& resultSet, const ElementType* vec, const SearchParams& /*searchParams*/) CV_OVERRIDE
     {
         ElementType* data = dataset_.data;
         for (size_t i = 0; i < dataset_.rows; ++i, data += dataset_.cols) {
@@ -112,7 +112,7 @@ public:
         }
     }
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return index_params_;
     }

modules/flann/include/opencv2/flann/lsh_index.h

@@ -107,7 +107,7 @@ public:
     /**
      * Builds the index
      */
-    void buildIndex()
+    void buildIndex() CV_OVERRIDE
     {
         tables_.resize(table_number_);
         for (unsigned int i = 0; i < table_number_; ++i) {
@@ -119,13 +119,13 @@ public:
         }
     }
 
-    flann_algorithm_t getType() const
+    flann_algorithm_t getType() const CV_OVERRIDE
     {
         return FLANN_INDEX_LSH;
     }
 
 
-    void saveIndex(FILE* stream)
+    void saveIndex(FILE* stream) CV_OVERRIDE
     {
         save_value(stream,table_number_);
         save_value(stream,key_size_);
@@ -133,7 +133,7 @@ public:
         save_value(stream, dataset_);
     }
 
-    void loadIndex(FILE* stream)
+    void loadIndex(FILE* stream) CV_OVERRIDE
     {
         load_value(stream, table_number_);
         load_value(stream, key_size_);
@@ -151,7 +151,7 @@ public:
     /**
      *  Returns size of index.
      */
-    size_t size() const
+    size_t size() const CV_OVERRIDE
     {
         return dataset_.rows;
     }
@@ -159,7 +159,7 @@ public:
     /**
      * Returns the length of an index feature.
      */
-    size_t veclen() const
+    size_t veclen() const CV_OVERRIDE
     {
         return feature_size_;
     }
@@ -168,13 +168,13 @@ public:
      * Computes the index memory usage
      * Returns: memory used by the index
      */
-    int usedMemory() const
+    int usedMemory() const CV_OVERRIDE
     {
         return (int)(dataset_.rows * sizeof(int));
     }
 
 
-    IndexParams getParameters() const
+    IndexParams getParameters() const CV_OVERRIDE
     {
         return index_params_;
     }
@@ -187,7 +187,7 @@ public:
      * \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)
+    virtual void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params) CV_OVERRIDE
     {
         assert(queries.cols == veclen());
         assert(indices.rows >= queries.rows);
@@ -217,7 +217,7 @@ public:
      *     vec = the vector for which to search the nearest neighbors
      *     maxCheck = the maximum number of restarts (in a best-bin-first manner)
      */
-    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& /*searchParams*/)
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& /*searchParams*/) CV_OVERRIDE
     {
         getNeighbors(vec, result);
     }

modules/flann/include/opencv2/flann/result_set.h

@@ -109,13 +109,13 @@ public:
         return count;
     }
 
-    bool full() const
+    bool full() const CV_OVERRIDE
     {
         return count == capacity;
     }
 
 
-    void addPoint(DistanceType dist, int index)
+    void addPoint(DistanceType dist, int index) CV_OVERRIDE
     {
         if (dist >= worst_distance_) return;
         int i;
@@ -139,7 +139,7 @@ public:
         worst_distance_ = dists[capacity-1];
     }
 
-    DistanceType worstDist() const
+    DistanceType worstDist() const CV_OVERRIDE
     {
         return worst_distance_;
     }
@@ -176,13 +176,13 @@ public:
         return count;
     }
 
-    bool full() const
+    bool full() const CV_OVERRIDE
     {
         return count == capacity;
     }
 
 
-    void addPoint(DistanceType dist, int index)
+    void addPoint(DistanceType dist, int index) CV_OVERRIDE
     {
         if (dist >= worst_distance_) return;
         int i;
@@ -215,7 +215,7 @@ public:
         worst_distance_ = dists[capacity-1];
     }
 
-    DistanceType worstDist() const
+    DistanceType worstDist() const CV_OVERRIDE
     {
         return worst_distance_;
     }
@@ -310,7 +310,7 @@ public:
     /** Check the status of the set
      * @return true if we have k NN
      */
-    inline bool full() const
+    inline bool full() const CV_OVERRIDE
     {
         return is_full_;
     }
@@ -365,7 +365,7 @@ public:
      * If we don't have enough neighbors, it returns the max possible value
      * @return
      */
-    inline DistanceType worstDist() const
+    inline DistanceType worstDist() const CV_OVERRIDE
     {
         return worst_distance_;
     }
@@ -402,7 +402,7 @@ public:
      * @param dist distance for that neighbor
      * @param index index of that neighbor
      */
-    inline void addPoint(DistanceType dist, int index)
+    inline void addPoint(DistanceType dist, int index) CV_OVERRIDE
     {
         // Don't do anything if we are worse than the worst
         if (dist >= worst_distance_) return;
@@ -422,7 +422,7 @@ public:
 
     /** Remove all elements in the set
      */
-    void clear()
+    void clear() CV_OVERRIDE
     {
         dist_indices_.clear();
         worst_distance_ = std::numeric_limits<DistanceType>::max();
@@ -461,14 +461,14 @@ public:
      * @param dist distance for that neighbor
      * @param index index of that neighbor
      */
-    void addPoint(DistanceType dist, int index)
+    void addPoint(DistanceType dist, int index) CV_OVERRIDE
     {
         if (dist <= radius_) dist_indices_.insert(DistIndex(dist, index));
     }
 
     /** Remove all elements in the set
      */
-    inline void clear()
+    inline void clear() CV_OVERRIDE
     {
         dist_indices_.clear();
     }
@@ -477,7 +477,7 @@ public:
     /** Check the status of the set
      * @return alwys false
      */
-    inline bool full() const
+    inline bool full() const CV_OVERRIDE
     {
         return true;
     }
@@ -486,7 +486,7 @@ public:
      * If we don't have enough neighbors, it returns the max possible value
      * @return
      */
-    inline DistanceType worstDist() const
+    inline DistanceType worstDist() const CV_OVERRIDE
     {
         return radius_;
     }