Merge pull request #79 from taka-no-me:warnings

This commit is contained in:
Andrey Kamaev 2012-10-22 20:56:53 +04:00
commit 781d89829f
16 changed files with 76 additions and 38 deletions

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@ -182,10 +182,20 @@ MACRO(ADD_PRECOMPILED_HEADER_TO_TARGET _targetName _input _pch_output_to_use )
_PCH_GET_TARGET_COMPILE_FLAGS(_target_cflags ${_name} ${_pch_output_to_use} ${_dowarn})
#MESSAGE("Add flags ${_target_cflags} to ${_targetName} " )
SET_TARGET_PROPERTIES(${_targetName}
PROPERTIES
COMPILE_FLAGS ${_target_cflags}
)
GET_TARGET_PROPERTY(_sources ${_targetName} SOURCES)
FOREACH(src ${_sources})
if(NOT "${src}" MATCHES "\\.mm$")
get_source_file_property(_flags "${src}" COMPILE_FLAGS)
if(_flags)
set(_flags "${_flags} ${_target_cflags}")
else()
set(_flags "${_target_cflags}")
endif()
set_source_files_properties("${src}" PROPERTIES COMPILE_FLAGS "${_flags}")
endif()
ENDFOREACH()
ADD_CUSTOM_TARGET(pch_Generate_${_targetName}
DEPENDS ${_pch_output_to_use}

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@ -59,6 +59,9 @@
# ifdef ANDROID
template <typename Scalar> Scalar log2(Scalar v) { using std::log; return log(v)/log(Scalar(2)); }
# endif
# if defined __GNUC__ && defined __APPLE__
# pragma GCC diagnostic ignored "-Wshadow"
# endif
# include <unsupported/Eigen/MatrixFunctions>
# include <Eigen/Dense>
#endif

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@ -86,6 +86,11 @@
#include <limits>
#ifdef _MSC_VER
# pragma warning(push)
# pragma warning(disable:4127) //conditional expression is constant
#endif
namespace cv
{
@ -3950,5 +3955,9 @@ template<typename _Tp> inline void AlgorithmInfo::addParam(Algorithm& algo, cons
}
#ifdef _MSC_VER
# pragma warning(pop)
#endif
#endif // __cplusplus
#endif

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@ -2813,7 +2813,7 @@ PCA::PCA(InputArray data, InputArray _mean, int flags, int maxComponents)
PCA::PCA(InputArray data, InputArray _mean, int flags, double retainedVariance)
{
operator()(data, _mean, flags, retainedVariance);
computeVar(data, _mean, flags, retainedVariance);
}
PCA& PCA::operator()(InputArray _data, InputArray __mean, int flags, int maxComponents)
@ -3077,7 +3077,7 @@ void cv::PCAComputeVar(InputArray data, InputOutputArray mean,
OutputArray eigenvectors, double retainedVariance)
{
PCA pca;
pca(data, mean, 0, retainedVariance);
pca.computeVar(data, mean, 0, retainedVariance);
pca.mean.copyTo(mean);
pca.eigenvectors.copyTo(eigenvectors);
}

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@ -362,8 +362,8 @@ void cv::setNumThreads( int threads )
else if (pplScheduler == 0 || 1 + pplScheduler->GetNumberOfVirtualProcessors() != (unsigned int)threads)
{
pplScheduler = Concurrency::Scheduler::Create(Concurrency::SchedulerPolicy(2,
Concurrency::PolicyElementKey::MinConcurrency, threads-1,
Concurrency::PolicyElementKey::MaxConcurrency, threads-1));
Concurrency::MinConcurrency, threads-1,
Concurrency::MaxConcurrency, threads-1));
}
#endif

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@ -426,7 +426,7 @@ protected:
}
// 3. check C++ PCA w/retainedVariance
cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, retainedVariance );
cPCA.computeVar( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, retainedVariance );
diffPrjEps = 1, diffBackPrjEps = 1;
Mat rvPrjTestPoints = cPCA.project(rTestPoints.t());

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@ -500,7 +500,7 @@ int runRadiusSearch_(void* index, const Mat& query, Mat& indices, Mat& dists,
::cvflann::Matrix<DistanceType> _dists((DistanceType*)dists.data, dists.rows, dists.cols);
return ((IndexType*)index)->radiusSearch(_query, _indices, _dists,
saturate_cast<DistanceType>(radius),
saturate_cast<float>(radius),
(const ::cvflann::SearchParams&)get_params(params));
}

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@ -503,6 +503,9 @@ bool CvCaptureCAM::setProperty(int property_id, double value) {
didOutputVideoFrame:(CVImageBufferRef)videoFrame
withSampleBuffer:(QTSampleBuffer *)sampleBuffer
fromConnection:(QTCaptureConnection *)connection {
(void)captureOutput;
(void)sampleBuffer;
(void)connection;
CVBufferRetain(videoFrame);
CVImageBufferRef imageBufferToRelease = mCurrentImageBuffer;
@ -519,6 +522,9 @@ bool CvCaptureCAM::setProperty(int property_id, double value) {
- (void)captureOutput:(QTCaptureOutput *)captureOutput
didDropVideoFrameWithSampleBuffer:(QTSampleBuffer *)sampleBuffer
fromConnection:(QTCaptureConnection *)connection {
(void)captureOutput;
(void)sampleBuffer;
(void)connection;
cout << "Camera dropped frame!" << endl;
}

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@ -48,6 +48,10 @@
# pragma warning( disable: 4100 4244 4267 )
#endif
#if defined __GNUC__ && defined __APPLE__
# pragma GCC diagnostic ignored "-Wshadow"
#endif
#include <ImfHeader.h>
#include <ImfInputFile.h>
#include <ImfOutputFile.h>

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@ -45,6 +45,10 @@
#ifdef HAVE_OPENEXR
#if defined __GNUC__ && defined __APPLE__
# pragma GCC diagnostic ignored "-Wshadow"
#endif
#include <ImfChromaticities.h>
#include <ImfInputFile.h>
#include <ImfChannelList.h>

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@ -136,7 +136,7 @@ static bool wasInitialized = false;
}
}*/
CV_IMPL int cvInitSystem( int argc, char** argv)
CV_IMPL int cvInitSystem( int , char** )
{
//cout << "cvInitSystem" << endl;
wasInitialized = true;
@ -159,7 +159,7 @@ CV_IMPL int cvInitSystem( int argc, char** argv)
return 0;
}
CVWindow *cvGetWindow(const char *name) {
static CVWindow *cvGetWindow(const char *name) {
//cout << "cvGetWindow" << endl;
NSAutoreleasePool* localpool = [[NSAutoreleasePool alloc] init];
NSString *cvname = [NSString stringWithFormat:@"%s", name];
@ -614,6 +614,7 @@ void cvSetModeWindow_COCOA( const char* name, double prop_value )
@synthesize status;
- (void)cvSendMouseEvent:(NSEvent *)event type:(int)type flags:(int)flags {
(void)event;
//cout << "cvSendMouseEvent" << endl;
NSPoint mp = [NSEvent mouseLocation];
//NSRect visible = [[self contentView] frame];
@ -924,6 +925,7 @@ void cvSetModeWindow_COCOA( const char* name, double prop_value )
}
- (void)sliderChanged:(NSNotification *)notification {
(void)notification;
int pos = [slider intValue];
if(value)
*value = pos;

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@ -1387,8 +1387,8 @@ struct RGB2Lab_f
C6 = coeffs[6], C7 = coeffs[7], C8 = coeffs[8];
n *= 3;
static const float _1_3 = 1.0 / 3.0;
static const double _a = 16.0 / 116;
static const float _1_3 = 1.0f / 3.0f;
static const float _a = 16.0f / 116.0f;
for (i = 0; i < n; i += 3, src += scn )
{
float R = clip(src[0]);
@ -1409,11 +1409,11 @@ struct RGB2Lab_f
float Y = R*C3 + G*C4 + B*C5;
float Z = R*C6 + G*C7 + B*C8;
float FX = X > 0.008856 ? pow(X, _1_3) : (7.787f * X + _a);
float FY = Y > 0.008856 ? pow(Y, _1_3) : (7.787f * Y + _a);
float FZ = Z > 0.008856 ? pow(Z, _1_3) : (7.787f * Z + _a);
float FX = X > 0.008856f ? pow(X, _1_3) : (7.787f * X + _a);
float FY = Y > 0.008856f ? pow(Y, _1_3) : (7.787f * Y + _a);
float FZ = Z > 0.008856f ? pow(Z, _1_3) : (7.787f * Z + _a);
float L = Y > 0.008856 ? (116.f * FY - 16.f) : (903.3 * Y);
float L = Y > 0.008856f ? (116.f * FY - 16.f) : (903.3f * Y);
float a = 500.f * (FX - FY);
float b = 200.f * (FY - FZ);

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@ -169,7 +169,7 @@ private:
__instype *split = median;
for (; split != last && deref(ctor(*split), dim) ==
deref(ctor(*median), dim); ++split);
deref(ctor(*median), dim); ++split) {}
if (split == last) { // leaf
int nexti = -1;
@ -387,9 +387,8 @@ public:
// ret_nn_pq is an array containing the (at most) k nearest neighbors
// (see bbf_nn structure def above).
template < class __desctype >
int find_nn_bbf(const __desctype * d,
int k, int emax,
bbf_nn_pqueue & ret_nn_pq) const {
int find_nn_bbf(const __desctype * d, int k, int emax, bbf_nn_pqueue & ret_nn_pq) const
{
assert(k > 0);
ret_nn_pq.clear();
@ -400,7 +399,8 @@ public:
// iterate while queue non-empty and emax>0
tmp_pq.clear();
tmp_pq.push_back(bbf_node(root_node, 0));
while (tmp_pq.size() && emax > 0) {
while (tmp_pq.size() && emax > 0)
{
// from node nearest query point d, run to leaf
std::pop_heap(tmp_pq.begin(), tmp_pq.end());
@ -408,11 +408,10 @@ public:
tmp_pq.erase(tmp_pq.end() - 1);
int i;
for (i = bbf.node;
i != -1 && nodes[i].dim >= 0;
i = bbf_branch(i, d, tmp_pq));
for (i = bbf.node; i != -1 && nodes[i].dim >= 0; i = bbf_branch(i, d, tmp_pq)) {}
if (i != -1) {
if (i != -1)
{
// add points in leaf/bin to ret_nn_pq
do {

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@ -414,7 +414,7 @@ static void icvFindStereoCorrespondenceByBirchfieldDP( uchar* src1, uchar* src2,
for( x = 1; x < imgW; x++ )
{
i = x - 1;
for( ; x < imgW && dest[y*widthStep+x] == dest[y*widthStep+x-1]; x++ );
for( ; x < imgW && dest[y*widthStep+x] == dest[y*widthStep+x-1]; x++ ) {}
s = x - i;
for( ; i < x; i++ )
{

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@ -633,7 +633,7 @@ static CvTestSeqElem* icvTestSeqReadElemOne(CvTestSeq_* pTS, CvFileStorage* fs,
for(i0=0, i1=1; i1<KeyFrameNum;)
{
for(i1=i0+1; i1<KeyFrameNum && KeyFrames[i1]<0; i1++);
for(i1=i0+1; i1<KeyFrameNum && KeyFrames[i1]<0; i1++) {}
assert(i1<KeyFrameNum);
assert(i1>i0);
@ -779,7 +779,7 @@ static CvTestSeqElem* icvTestSeqReadElemAll(CvTestSeq_* pTS, CvFileStorage* fs,
}
/* Find last element: */
for(pElemLast=pElemNew;pElemLast && pElemLast->next;pElemLast= pElemLast->next);
for(pElemLast=pElemNew;pElemLast && pElemLast->next;pElemLast= pElemLast->next) {}
} /* Next element. */
} /* Read all element in sequence. */
@ -842,7 +842,7 @@ CvTestSeq* cvCreateTestSeq(char* pConfigfile, char** videos, int numvideo, float
else
{
CvTestSeqElem* p = NULL;
for(p=pTS->pElemList;p->next;p=p->next);
for(p=pTS->pElemList;p->next;p=p->next) {}
p->next = pElemNew;
}
} /* Read all videos. */

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@ -3829,8 +3829,9 @@ static int zero = 0;
coeff_usage = CV_VALUE; \
else if ((length == alpha.count) && (alpha.count == beta.count) && (beta.count == gamma.count)) \
coeff_usage = CV_ARRAY; \
else \
return (PyObject*)failmsg("SnakeImage weights invalid"); \
else { \
failmsg("SnakeImage weights invalid"); \
return (PyObject*)0; } \
cvSnakeImage(image, points, length, a, b, g, coeff_usage, win, criteria, calc_gradient); \
} while (0)