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Fixed several GCC 5.x warnings

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This commit is contained in:
Maksim Shabunin 2016-08-31 23:12:52 +03:00
parent 595fd2757c
commit dc704d77ac
7 changed files with 121 additions and 153 deletions
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2
3rdparty/libtiff/CMakeLists.txt vendored
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@ -95,7 +95,7 @@ ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4267 /wd4305 /wd4306) # vs2008 Win64
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4703) # vs2012 ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4703) # vs2012
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4456 /wd4457 /wd4312) # vs2015 ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4456 /wd4457 /wd4312) # vs2015
ocv_warnings_disable(CMAKE_C_FLAGS /wd4267 /wd4244 /wd4018) ocv_warnings_disable(CMAKE_C_FLAGS /wd4267 /wd4244 /wd4018 /wd4311 /wd4312)
if(UNIX AND (CMAKE_COMPILER_IS_GNUCXX OR CV_ICC)) if(UNIX AND (CMAKE_COMPILER_IS_GNUCXX OR CV_ICC))
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fPIC") set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fPIC")

1
cmake/OpenCVCompilerOptions.cmake
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@ -97,6 +97,7 @@ if(CMAKE_COMPILER_IS_GNUCXX)
add_extra_compiler_option(-Wno-narrowing) add_extra_compiler_option(-Wno-narrowing)
add_extra_compiler_option(-Wno-delete-non-virtual-dtor) add_extra_compiler_option(-Wno-delete-non-virtual-dtor)
add_extra_compiler_option(-Wno-unnamed-type-template-args) add_extra_compiler_option(-Wno-unnamed-type-template-args)
add_extra_compiler_option(-Wno-comment)
endif() endif()
add_extra_compiler_option(-fdiagnostics-show-option) add_extra_compiler_option(-fdiagnostics-show-option)

2
modules/core/include/opencv2/core/utility.hpp
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@ -1126,7 +1126,7 @@ CV_EXPORTS InstrNode* getTrace();
CV_EXPORTS void resetTrace(); CV_EXPORTS void resetTrace();
CV_EXPORTS void setFlags(int modeFlags); CV_EXPORTS void setFlags(int modeFlags);
CV_EXPORTS int getFlags(); CV_EXPORTS int getFlags();
}; }
} //namespace cv } //namespace cv

3
modules/core/perf/perf_umat.cpp
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@ -13,7 +13,6 @@ using namespace ::testing;
using std::tr1::tuple; using std::tr1::tuple;
using std::tr1::get; using std::tr1::get;
namespace {
struct OpenCLState struct OpenCLState
{ {
@ -64,5 +63,3 @@ OCL_PERF_TEST_P(UMatTest, CustomPtr, Combine(Values(sz1080p, sz2160p), Bool(), :
SANITY_CHECK_NOTHING(); SANITY_CHECK_NOTHING();
} }
} // namespace cvtest

2
modules/core/test/test_ds.cpp
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@ -56,7 +56,7 @@ static void cvTsSimpleSeqShiftAndCopy( CvTsSimpleSeq* seq, int from_idx, int to_
(seq->count - from_idx)*elem_size ); (seq->count - from_idx)*elem_size );
} }
seq->count += to_idx - from_idx; seq->count += to_idx - from_idx;
if( elem && to_idx > from_idx ) if( elem )
memcpy( seq->array + from_idx*elem_size, elem, (to_idx - from_idx)*elem_size ); memcpy( seq->array + from_idx*elem_size, elem, (to_idx - from_idx)*elem_size );
} }

2
modules/features2d/include/opencv2/features2d.hpp
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@ -1022,7 +1022,7 @@ protected:
/** @brief Flann-based descriptor matcher. /** @brief Flann-based descriptor matcher.
This matcher trains flann::Index_ on a train descriptor collection and calls its nearest search This matcher trains cv::flann::Index on a train descriptor collection and calls its nearest search
methods to find the best matches. So, this matcher may be faster when matching a large train methods to find the best matches. So, this matcher may be faster when matching a large train
collection than the brute force matcher. FlannBasedMatcher does not support masking permissible collection than the brute force matcher. FlannBasedMatcher does not support masking permissible
matches of descriptor sets because flann::Index does not support this. : matches of descriptor sets because flann::Index does not support this. :

262
modules/flann/include/opencv2/flann.hpp
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@ -338,164 +338,134 @@ int GenericIndex<Distance>::radiusSearch(const Mat& query, Mat& indices, Mat& di
* @deprecated Use GenericIndex class instead * @deprecated Use GenericIndex class instead
*/ */
template <typename T> template <typename T>
class class Index_
#ifndef _MSC_VER {
FLANN_DEPRECATED
#endif
Index_ {
public: public:
typedef typename L2<T>::ElementType ElementType; typedef typename L2<T>::ElementType ElementType;
typedef typename L2<T>::ResultType DistanceType; typedef typename L2<T>::ResultType DistanceType;
Index_(const Mat& features, const ::cvflann::IndexParams& params); FLANN_DEPRECATED Index_(const Mat& dataset, const ::cvflann::IndexParams& params)
~Index_();
void knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params);
void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params);
int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params);
int radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& params);
void save(String filename)
{
if (nnIndex_L1) nnIndex_L1->save(filename);
if (nnIndex_L2) nnIndex_L2->save(filename);
}
int veclen() const
{ {
if (nnIndex_L1) return nnIndex_L1->veclen(); printf("[WARNING] The cv::flann::Index_<T> class is deperecated, use cv::flann::GenericIndex<Distance> instead\n");
if (nnIndex_L2) return nnIndex_L2->veclen();
}
int size() const CV_Assert(dataset.type() == CvType<ElementType>::type());
CV_Assert(dataset.isContinuous());
::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);
if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
nnIndex_L1 = NULL;
nnIndex_L2 = new ::cvflann::Index< L2<ElementType> >(m_dataset, params);
}
else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
nnIndex_L1 = new ::cvflann::Index< L1<ElementType> >(m_dataset, params);
nnIndex_L2 = NULL;
}
else {
printf("[ERROR] cv::flann::Index_<T> only provides backwards compatibility for the L1 and L2 distances. "
"For other distance types you must use cv::flann::GenericIndex<Distance>\n");
CV_Assert(0);
}
if (nnIndex_L1) nnIndex_L1->buildIndex();
if (nnIndex_L2) nnIndex_L2->buildIndex();
}
FLANN_DEPRECATED ~Index_()
{ {
if (nnIndex_L1) return nnIndex_L1->size(); if (nnIndex_L1) delete nnIndex_L1;
if (nnIndex_L2) return nnIndex_L2->size(); if (nnIndex_L2) delete nnIndex_L2;
} }
::cvflann::IndexParams getParameters() FLANN_DEPRECATED void knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
{ {
if (nnIndex_L1) return nnIndex_L1->getParameters(); ::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
if (nnIndex_L2) return nnIndex_L2->getParameters(); ::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
} if (nnIndex_L1) nnIndex_L1->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
if (nnIndex_L2) nnIndex_L2->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
}
FLANN_DEPRECATED void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
CV_Assert(queries.type() == CvType<ElementType>::type());
CV_Assert(queries.isContinuous());
::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);
FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters() CV_Assert(indices.type() == CV_32S);
{ CV_Assert(indices.isContinuous());
if (nnIndex_L1) return nnIndex_L1->getIndexParameters(); ::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
if (nnIndex_L2) return nnIndex_L2->getIndexParameters();
} CV_Assert(dists.type() == CvType<DistanceType>::type());
CV_Assert(dists.isContinuous());
::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
if (nnIndex_L1) nnIndex_L1->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
if (nnIndex_L2) nnIndex_L2->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
}
FLANN_DEPRECATED int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
FLANN_DEPRECATED int radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
CV_Assert(query.type() == CvType<ElementType>::type());
CV_Assert(query.isContinuous());
::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);
CV_Assert(indices.type() == CV_32S);
CV_Assert(indices.isContinuous());
::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
CV_Assert(dists.type() == CvType<DistanceType>::type());
CV_Assert(dists.isContinuous());
::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
FLANN_DEPRECATED void save(String filename)
{
if (nnIndex_L1) nnIndex_L1->save(filename);
if (nnIndex_L2) nnIndex_L2->save(filename);
}
FLANN_DEPRECATED int veclen() const
{
if (nnIndex_L1) return nnIndex_L1->veclen();
if (nnIndex_L2) return nnIndex_L2->veclen();
}
FLANN_DEPRECATED int size() const
{
if (nnIndex_L1) return nnIndex_L1->size();
if (nnIndex_L2) return nnIndex_L2->size();
}
FLANN_DEPRECATED ::cvflann::IndexParams getParameters()
{
if (nnIndex_L1) return nnIndex_L1->getParameters();
if (nnIndex_L2) return nnIndex_L2->getParameters();
}
FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters()
{
if (nnIndex_L1) return nnIndex_L1->getIndexParameters();
if (nnIndex_L2) return nnIndex_L2->getIndexParameters();
}
private: private:
// providing backwards compatibility for L2 and L1 distances (most common) // providing backwards compatibility for L2 and L1 distances (most common)
::cvflann::Index< L2<ElementType> >* nnIndex_L2; ::cvflann::Index< L2<ElementType> >* nnIndex_L2;
::cvflann::Index< L1<ElementType> >* nnIndex_L1; ::cvflann::Index< L1<ElementType> >* nnIndex_L1;
}; };
#ifdef _MSC_VER
template <typename T>
class FLANN_DEPRECATED Index_;
#endif
//! @cond IGNORED
template <typename T>
Index_<T>::Index_(const Mat& dataset, const ::cvflann::IndexParams& params)
{
printf("[WARNING] The cv::flann::Index_<T> class is deperecated, use cv::flann::GenericIndex<Distance> instead\n");
CV_Assert(dataset.type() == CvType<ElementType>::type());
CV_Assert(dataset.isContinuous());
::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);
if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
nnIndex_L1 = NULL;
nnIndex_L2 = new ::cvflann::Index< L2<ElementType> >(m_dataset, params);
}
else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
nnIndex_L1 = new ::cvflann::Index< L1<ElementType> >(m_dataset, params);
nnIndex_L2 = NULL;
}
else {
printf("[ERROR] cv::flann::Index_<T> only provides backwards compatibility for the L1 and L2 distances. "
"For other distance types you must use cv::flann::GenericIndex<Distance>\n");
CV_Assert(0);
}
if (nnIndex_L1) nnIndex_L1->buildIndex();
if (nnIndex_L2) nnIndex_L2->buildIndex();
}
template <typename T>
Index_<T>::~Index_()
{
if (nnIndex_L1) delete nnIndex_L1;
if (nnIndex_L2) delete nnIndex_L2;
}
template <typename T>
void Index_<T>::knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
if (nnIndex_L1) nnIndex_L1->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
if (nnIndex_L2) nnIndex_L2->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
}
template <typename T>
void Index_<T>::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
CV_Assert(queries.type() == CvType<ElementType>::type());
CV_Assert(queries.isContinuous());
::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);
CV_Assert(indices.type() == CV_32S);
CV_Assert(indices.isContinuous());
::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
CV_Assert(dists.type() == CvType<DistanceType>::type());
CV_Assert(dists.isContinuous());
::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
if (nnIndex_L1) nnIndex_L1->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
if (nnIndex_L2) nnIndex_L2->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
}
template <typename T>
int Index_<T>::radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
template <typename T>
int Index_<T>::radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
CV_Assert(query.type() == CvType<ElementType>::type());
CV_Assert(query.isContinuous());
::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);
CV_Assert(indices.type() == CV_32S);
CV_Assert(indices.isContinuous());
::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
CV_Assert(dists.type() == CvType<DistanceType>::type());
CV_Assert(dists.isContinuous());
::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
//! @endcond
/** @brief Clusters features using hierarchical k-means algorithm. /** @brief Clusters features using hierarchical k-means algorithm.