Fixed several GCC 5.x warnings
This commit is contained in:
parent
595fd2757c
commit
dc704d77ac
2
3rdparty/libtiff/CMakeLists.txt
vendored
2
3rdparty/libtiff/CMakeLists.txt
vendored
@ -95,7 +95,7 @@ ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4267 /wd4305 /wd4306) # vs2008 Win64
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ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4703) # vs2012
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ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4456 /wd4457 /wd4312) # vs2015
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ocv_warnings_disable(CMAKE_C_FLAGS /wd4267 /wd4244 /wd4018)
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ocv_warnings_disable(CMAKE_C_FLAGS /wd4267 /wd4244 /wd4018 /wd4311 /wd4312)
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if(UNIX AND (CMAKE_COMPILER_IS_GNUCXX OR CV_ICC))
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set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fPIC")
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@ -97,6 +97,7 @@ if(CMAKE_COMPILER_IS_GNUCXX)
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add_extra_compiler_option(-Wno-narrowing)
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add_extra_compiler_option(-Wno-delete-non-virtual-dtor)
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add_extra_compiler_option(-Wno-unnamed-type-template-args)
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add_extra_compiler_option(-Wno-comment)
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endif()
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add_extra_compiler_option(-fdiagnostics-show-option)
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@ -1126,7 +1126,7 @@ CV_EXPORTS InstrNode* getTrace();
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CV_EXPORTS void resetTrace();
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CV_EXPORTS void setFlags(int modeFlags);
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CV_EXPORTS int getFlags();
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};
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}
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} //namespace cv
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@ -13,7 +13,6 @@ using namespace ::testing;
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using std::tr1::tuple;
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using std::tr1::get;
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namespace {
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struct OpenCLState
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{
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@ -64,5 +63,3 @@ OCL_PERF_TEST_P(UMatTest, CustomPtr, Combine(Values(sz1080p, sz2160p), Bool(), :
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SANITY_CHECK_NOTHING();
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}
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} // namespace cvtest
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@ -56,7 +56,7 @@ static void cvTsSimpleSeqShiftAndCopy( CvTsSimpleSeq* seq, int from_idx, int to_
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(seq->count - from_idx)*elem_size );
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}
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seq->count += to_idx - from_idx;
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if( elem && to_idx > from_idx )
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if( elem )
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memcpy( seq->array + from_idx*elem_size, elem, (to_idx - from_idx)*elem_size );
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}
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@ -1022,7 +1022,7 @@ protected:
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/** @brief Flann-based descriptor matcher.
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This matcher trains flann::Index_ on a train descriptor collection and calls its nearest search
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This matcher trains cv::flann::Index on a train descriptor collection and calls its nearest search
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methods to find the best matches. So, this matcher may be faster when matching a large train
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collection than the brute force matcher. FlannBasedMatcher does not support masking permissible
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matches of descriptor sets because flann::Index does not support this. :
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@ -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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