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fixed defects from Xcode

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This commit is contained in:
Ilya Lavrenov 2014-02-23 21:07:20 +04:00
parent 32eb38ec98
commit ce0557ebb8
11 changed files with 23 additions and 29 deletions
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1
modules/calib3d/src/circlesgrid.cpp
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@ -218,6 +218,7 @@ void CirclesGridClusterFinder::findCorners(const std::vector<cv::Point2f> &hull2
void CirclesGridClusterFinder::findOutsideCorners(const std::vector<cv::Point2f> &corners, std::vector<cv::Point2f> &outsideCorners)
{
CV_Assert(!corners.empty());
outsideCorners.clear();
//find two pairs of the most nearest corners
int i, j, n = (int)corners.size();

2
modules/calib3d/test/test_chesscorners.cpp
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@ -311,7 +311,7 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
if (count != 0)
sum_error /= count;
ts->printf(cvtest::TS::LOG, "Average error is %f\n", sum_error);
ts->printf(cvtest::TS::LOG, "Average error is %f (%d patterns have been found)\n", sum_error, count);
}
double calcErrorMinError(const Size& cornSz, const vector<Point2f>& corners_found, const vector<Point2f>& corners_generated)

3
modules/core/src/copy.cpp
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@ -353,7 +353,7 @@ Mat& Mat::operator = (const Scalar& s)
Mat& Mat::setTo(InputArray _value, InputArray _mask)
{
if( !data )
if( empty() )
return *this;
Mat value = _value.getMat(), mask = _mask.getMat();
@ -632,6 +632,7 @@ int cv::borderInterpolate( int p, int len, int borderType )
}
else if( borderType == BORDER_WRAP )
{
CV_Assert(len > 0);
if( p < 0 )
p -= ((p-len+1)/len)*len;
if( p >= len )

1
modules/core/src/system.cpp
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@ -426,6 +426,7 @@ String format( const char* fmt, ... )
String s(len, '\0');
va_start(va, fmt);
len = vsnprintf((char*)s.c_str(), len + 1, fmt, va);
(void)len;
va_end(va);
return s;
}

2
modules/imgproc/src/accum.cpp
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@ -408,7 +408,7 @@ static bool ocl_accumulate( InputArray _src, InputArray _src2, InputOutputArray
argidx = k.set(argidx, alpha);
}
if (haveMask)
argidx = k.set(argidx, maskarg);
k.set(argidx, maskarg);
size_t globalsize[2] = { src.cols, src.rows };
return k.run(2, globalsize, NULL, false);

12
modules/imgproc/src/clahe.cpp
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@ -83,11 +83,9 @@ namespace clahe
idx = k.set(idx, tile_size);
idx = k.set(idx, tilesX);
idx = k.set(idx, clipLimit);
idx = k.set(idx, lutScale);
k.set(idx, lutScale);
if (!k.run(2, globalThreads, localThreads, false))
return false;
return true;
return k.run(2, globalThreads, localThreads, false);
}
static bool transform(cv::InputArray _src, cv::OutputArray _dst, cv::InputArray _lut,
@ -118,11 +116,9 @@ namespace clahe
idx = k.set(idx, src.rows);
idx = k.set(idx, tile_size);
idx = k.set(idx, tilesX);
idx = k.set(idx, tilesY);
k.set(idx, tilesY);
if (!k.run(2, globalThreads, localThreads, false))
return false;
return true;
return k.run(2, globalThreads, localThreads, false);
}
}

3
modules/objdetect/src/erfilter.cpp
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@ -294,7 +294,7 @@ void ERFilterNM::er_tree_extract( InputArray image )
push_new_component = false;
// explore the (remaining) edges to the neighbors to the current pixel
for (current_edge = current_edge; current_edge < 4; current_edge++)
for ( ; current_edge < 4; current_edge++)
{
int neighbour_pixel = current_pixel;
@ -1949,7 +1949,6 @@ private:
double (dissimilarity::*distfn) (const int_fast32_t, const int_fast32_t) const;
auto_array_ptr<double> precomputed;
double * precomputed2;
double * V;
const double * V_data;

6
modules/objdetect/test/test_cascadeandhog.cpp
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@ -574,7 +574,7 @@ public:
Size winStride = Size(), Size padding = Size(),
const vector<Point>& locations = vector<Point>()) const;
virtual void compute(const Mat& img, vector<float>& descriptors,
virtual void compute(InputArray img, vector<float>& descriptors,
Size winStride = Size(), Size padding = Size(),
const vector<Point>& locations = vector<Point>()) const;
@ -1107,9 +1107,11 @@ void HOGDescriptorTester::detect(const Mat& img, vector<Point>& hits, double hit
detect(img, hits, weightsV, hitThreshold, winStride, padding, locations);
}
void HOGDescriptorTester::compute(const Mat& img, vector<float>& descriptors,
void HOGDescriptorTester::compute(InputArray _img, vector<float>& descriptors,
Size winStride, Size padding, const vector<Point>& locations) const
{
Mat img = _img.getMat();
if( winStride == Size() )
winStride = cellSize;
Size cacheStride(gcd(winStride.width, blockStride.width),

1
modules/shape/src/scd_def.hpp
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@ -120,7 +120,6 @@ public:
private:
float minMatchCost;
float betaAdditional;
protected:
void buildCostMatrix(const cv::Mat& descriptors1, const cv::Mat& descriptors2,
cv::Mat& costMatrix, cv::Ptr<cv::HistogramCostExtractor>& comparer) const;

4
modules/video/src/bgfg_gaussmix2.cpp
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@ -779,7 +779,7 @@ bool BackgroundSubtractorMOG2Impl::ocl_apply(InputArray _image, OutputArray _fgm
idxArg = kernel_apply.set(idxArg, varMax);
idxArg = kernel_apply.set(idxArg, fVarInit);
idxArg = kernel_apply.set(idxArg, fTau);
idxArg = kernel_apply.set(idxArg, nShadowDetection);
kernel_apply.set(idxArg, nShadowDetection);
size_t globalsize[] = {frame.cols, frame.rows, 1};
@ -805,7 +805,7 @@ bool BackgroundSubtractorMOG2Impl::ocl_getBackgroundImage(OutputArray _backgroun
idxArg = kernel_getBg.set(idxArg, ocl::KernelArg::ReadOnlyNoSize(u_weight));
idxArg = kernel_getBg.set(idxArg, ocl::KernelArg::ReadOnlyNoSize(u_mean));
idxArg = kernel_getBg.set(idxArg, ocl::KernelArg::WriteOnlyNoSize(dst));
idxArg = kernel_getBg.set(idxArg, backgroundRatio);
kernel_getBg.set(idxArg, backgroundRatio);
size_t globalsize[2] = {u_bgmodelUsedModes.cols, u_bgmodelUsedModes.rows};

17
modules/video/src/optflowgf.cpp
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@ -857,7 +857,7 @@ private:
idxArg = kernel.set(idxArg, dst.cols);
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrReadOnly(m_gKer));
idxArg = kernel.set(idxArg, (int)ksizeHalf);
idxArg = kernel.set(idxArg, (void *)NULL, smem_size);
kernel.set(idxArg, (void *)NULL, smem_size);
return kernel.run(2, globalsize, localsize, false);
}
bool gaussianBlur5Ocl(const UMat &src, int ksizeHalf, UMat &dst)
@ -883,7 +883,7 @@ private:
idxArg = kernel.set(idxArg, src.cols);
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrReadOnly(m_gKer));
idxArg = kernel.set(idxArg, (int)ksizeHalf);
idxArg = kernel.set(idxArg, (void *)NULL, smem_size);
kernel.set(idxArg, (void *)NULL, smem_size);
return kernel.run(2, globalsize, localsize, false);
}
bool polynomialExpansionOcl(const UMat &src, UMat &dst)
@ -919,12 +919,7 @@ private:
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrReadOnly(m_xg));
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrReadOnly(m_xxg));
idxArg = kernel.set(idxArg, (void *)NULL, smem_size);
#if 0
if (useDouble)
idxArg = kernel.set(idxArg, (void *)m_igd, 4 * sizeof(double));
else
#endif
idxArg = kernel.set(idxArg, (void *)m_ig, 4 * sizeof(float));
kernel.set(idxArg, (void *)m_ig, 4 * sizeof(float));
return kernel.run(2, globalsize, localsize, false);
}
bool boxFilter5Ocl(const UMat &src, int ksizeHalf, UMat &dst)
@ -951,7 +946,7 @@ private:
idxArg = kernel.set(idxArg, height);
idxArg = kernel.set(idxArg, src.cols);
idxArg = kernel.set(idxArg, (int)ksizeHalf);
idxArg = kernel.set(idxArg, (void *)NULL, smem_size);
kernel.set(idxArg, (void *)NULL, smem_size);
return kernel.run(2, globalsize, localsize, false);
}
@ -976,7 +971,7 @@ private:
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrReadOnly(flowy));
idxArg = kernel.set(idxArg, (int)(flowy.step / flowy.elemSize()));
idxArg = kernel.set(idxArg, (int)flowy.rows);
idxArg = kernel.set(idxArg, (int)flowy.cols);
kernel.set(idxArg, (int)flowy.cols);
return kernel.run(2, globalsize, localsize, false);
}
bool updateMatricesOcl(const UMat &flowx, const UMat &flowy, const UMat &R0, const UMat &R1, UMat &M)
@ -1004,7 +999,7 @@ private:
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrReadOnly(R1));
idxArg = kernel.set(idxArg, (int)(R1.step / R1.elemSize()));
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrWriteOnly(M));
idxArg = kernel.set(idxArg, (int)(M.step / M.elemSize()));
kernel.set(idxArg, (int)(M.step / M.elemSize()));
return kernel.run(2, globalsize, localsize, false);
}