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https://github.com/opencv/opencv.git
synced 2026-07-31 08:13:04 +04:00
Fixed several GCC 5.x warnings
This commit is contained in:
Maksim Shabunin
@@ -338,164 +338,134 @@ int GenericIndex<Distance>::radiusSearch(const Mat& query, Mat& indices, Mat& di
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* @deprecated Use GenericIndex class instead
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*/
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template <typename T>
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class
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#ifndef _MSC_VER
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FLANN_DEPRECATED
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#endif
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Index_ {
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class Index_
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{
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public:
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typedef typename L2<T>::ElementType ElementType;
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typedef typename L2<T>::ResultType DistanceType;
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typedef typename L2<T>::ElementType ElementType;
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typedef typename L2<T>::ResultType DistanceType;
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Index_(const Mat& features, const ::cvflann::IndexParams& params);
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~Index_();
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void knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params);
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void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params);
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int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params);
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int radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& params);
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void save(String filename)
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{
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if (nnIndex_L1) nnIndex_L1->save(filename);
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if (nnIndex_L2) nnIndex_L2->save(filename);
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}
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int veclen() const
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FLANN_DEPRECATED Index_(const Mat& dataset, const ::cvflann::IndexParams& params)
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{
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if (nnIndex_L1) return nnIndex_L1->veclen();
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if (nnIndex_L2) return nnIndex_L2->veclen();
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}
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printf("[WARNING] The cv::flann::Index_<T> class is deperecated, use cv::flann::GenericIndex<Distance> instead\n");
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int size() const
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CV_Assert(dataset.type() == CvType<ElementType>::type());
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CV_Assert(dataset.isContinuous());
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::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);
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if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
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nnIndex_L1 = NULL;
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nnIndex_L2 = new ::cvflann::Index< L2<ElementType> >(m_dataset, params);
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}
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else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
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nnIndex_L1 = new ::cvflann::Index< L1<ElementType> >(m_dataset, params);
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nnIndex_L2 = NULL;
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}
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else {
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printf("[ERROR] cv::flann::Index_<T> only provides backwards compatibility for the L1 and L2 distances. "
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"For other distance types you must use cv::flann::GenericIndex<Distance>\n");
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CV_Assert(0);
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}
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if (nnIndex_L1) nnIndex_L1->buildIndex();
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if (nnIndex_L2) nnIndex_L2->buildIndex();
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}
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FLANN_DEPRECATED ~Index_()
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{
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if (nnIndex_L1) return nnIndex_L1->size();
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if (nnIndex_L2) return nnIndex_L2->size();
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}
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if (nnIndex_L1) delete nnIndex_L1;
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if (nnIndex_L2) delete nnIndex_L2;
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}
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::cvflann::IndexParams getParameters()
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{
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if (nnIndex_L1) return nnIndex_L1->getParameters();
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if (nnIndex_L2) return nnIndex_L2->getParameters();
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FLANN_DEPRECATED void knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
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{
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::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
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::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
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::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
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}
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if (nnIndex_L1) nnIndex_L1->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
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if (nnIndex_L2) nnIndex_L2->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
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}
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FLANN_DEPRECATED void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
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{
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CV_Assert(queries.type() == CvType<ElementType>::type());
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CV_Assert(queries.isContinuous());
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::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);
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FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters()
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{
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if (nnIndex_L1) return nnIndex_L1->getIndexParameters();
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if (nnIndex_L2) return nnIndex_L2->getIndexParameters();
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}
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CV_Assert(indices.type() == CV_32S);
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CV_Assert(indices.isContinuous());
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::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
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CV_Assert(dists.type() == CvType<DistanceType>::type());
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CV_Assert(dists.isContinuous());
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::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
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if (nnIndex_L1) nnIndex_L1->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
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if (nnIndex_L2) nnIndex_L2->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
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}
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FLANN_DEPRECATED int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
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{
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::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
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::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
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::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
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if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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}
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FLANN_DEPRECATED int radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
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{
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CV_Assert(query.type() == CvType<ElementType>::type());
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CV_Assert(query.isContinuous());
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::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);
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CV_Assert(indices.type() == CV_32S);
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CV_Assert(indices.isContinuous());
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::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
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CV_Assert(dists.type() == CvType<DistanceType>::type());
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CV_Assert(dists.isContinuous());
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::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
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if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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}
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FLANN_DEPRECATED void save(String filename)
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{
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if (nnIndex_L1) nnIndex_L1->save(filename);
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if (nnIndex_L2) nnIndex_L2->save(filename);
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}
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FLANN_DEPRECATED int veclen() const
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{
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if (nnIndex_L1) return nnIndex_L1->veclen();
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if (nnIndex_L2) return nnIndex_L2->veclen();
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}
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FLANN_DEPRECATED int size() const
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{
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if (nnIndex_L1) return nnIndex_L1->size();
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if (nnIndex_L2) return nnIndex_L2->size();
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}
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FLANN_DEPRECATED ::cvflann::IndexParams getParameters()
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{
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if (nnIndex_L1) return nnIndex_L1->getParameters();
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if (nnIndex_L2) return nnIndex_L2->getParameters();
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}
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FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters()
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{
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if (nnIndex_L1) return nnIndex_L1->getIndexParameters();
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if (nnIndex_L2) return nnIndex_L2->getIndexParameters();
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}
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private:
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// providing backwards compatibility for L2 and L1 distances (most common)
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::cvflann::Index< L2<ElementType> >* nnIndex_L2;
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::cvflann::Index< L1<ElementType> >* nnIndex_L1;
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// providing backwards compatibility for L2 and L1 distances (most common)
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::cvflann::Index< L2<ElementType> >* nnIndex_L2;
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::cvflann::Index< L1<ElementType> >* nnIndex_L1;
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};
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#ifdef _MSC_VER
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template <typename T>
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class FLANN_DEPRECATED Index_;
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#endif
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//! @cond IGNORED
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template <typename T>
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Index_<T>::Index_(const Mat& dataset, const ::cvflann::IndexParams& params)
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{
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printf("[WARNING] The cv::flann::Index_<T> class is deperecated, use cv::flann::GenericIndex<Distance> instead\n");
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CV_Assert(dataset.type() == CvType<ElementType>::type());
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CV_Assert(dataset.isContinuous());
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::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);
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if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
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nnIndex_L1 = NULL;
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nnIndex_L2 = new ::cvflann::Index< L2<ElementType> >(m_dataset, params);
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}
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else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
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nnIndex_L1 = new ::cvflann::Index< L1<ElementType> >(m_dataset, params);
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nnIndex_L2 = NULL;
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}
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else {
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printf("[ERROR] cv::flann::Index_<T> only provides backwards compatibility for the L1 and L2 distances. "
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"For other distance types you must use cv::flann::GenericIndex<Distance>\n");
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CV_Assert(0);
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}
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if (nnIndex_L1) nnIndex_L1->buildIndex();
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if (nnIndex_L2) nnIndex_L2->buildIndex();
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}
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template <typename T>
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Index_<T>::~Index_()
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{
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if (nnIndex_L1) delete nnIndex_L1;
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if (nnIndex_L2) delete nnIndex_L2;
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}
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template <typename T>
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void Index_<T>::knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
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{
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::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
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::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
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::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
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if (nnIndex_L1) nnIndex_L1->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
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if (nnIndex_L2) nnIndex_L2->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
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}
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template <typename T>
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void Index_<T>::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
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{
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CV_Assert(queries.type() == CvType<ElementType>::type());
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CV_Assert(queries.isContinuous());
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::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);
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CV_Assert(indices.type() == CV_32S);
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CV_Assert(indices.isContinuous());
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::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
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CV_Assert(dists.type() == CvType<DistanceType>::type());
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CV_Assert(dists.isContinuous());
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::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
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if (nnIndex_L1) nnIndex_L1->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
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if (nnIndex_L2) nnIndex_L2->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
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}
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template <typename T>
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int Index_<T>::radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
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{
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::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
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::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
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::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
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if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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}
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template <typename T>
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int Index_<T>::radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
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{
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CV_Assert(query.type() == CvType<ElementType>::type());
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CV_Assert(query.isContinuous());
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::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);
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CV_Assert(indices.type() == CV_32S);
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CV_Assert(indices.isContinuous());
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::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
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CV_Assert(dists.type() == CvType<DistanceType>::type());
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CV_Assert(dists.isContinuous());
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::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
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if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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}
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//! @endcond
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/** @brief Clusters features using hierarchical k-means algorithm.
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