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Fixing some static analysis issues

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This commit is contained in:
Maksim Shabunin
2017-06-26 14:09:21 +03:00
parent b991665b5d
commit 32d4af36e2
63 changed files with 238 additions and 94 deletions
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modules/imgproc/src/connectedcomponents.cpp
+2 -2
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@@ -95,8 +95,8 @@ namespace cv{
std::vector<Point2ui64> integrals;
int _nextLoc;
CCStatsOp(){}
CCStatsOp(OutputArray _statsv, OutputArray _centroidsv) : _mstatsv(&_statsv), _mcentroidsv(&_centroidsv){}
CCStatsOp() : _mstatsv(0), _mcentroidsv(0), _nextLoc(0) {}
CCStatsOp(OutputArray _statsv, OutputArray _centroidsv) : _mstatsv(&_statsv), _mcentroidsv(&_centroidsv), _nextLoc(0){}
inline
void init(int nlabels){
modules/imgproc/src/drawing.cpp
+3
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@@ -178,6 +178,9 @@ LineIterator::LineIterator(const Mat& img, Point pt1, Point pt2,
{
ptr = img.data;
err = plusDelta = minusDelta = plusStep = minusStep = count = 0;
ptr0 = 0;
step = 0;
elemSize = 0;
return;
}
}
modules/imgproc/src/filter.cpp
+22 -10
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@@ -77,6 +77,9 @@ FilterEngine::FilterEngine()
maxWidth = 0;
wholeSize = Size(-1,-1);
dx1 = 0;
borderElemSize = 0;
dx2 = 0;
}
@@ -87,6 +90,11 @@ FilterEngine::FilterEngine( const Ptr<BaseFilter>& _filter2D,
int _rowBorderType, int _columnBorderType,
const Scalar& _borderValue )
{
startY0 = 0;
endY = 0;
dstY = 0;
dx2 = 0;
rowCount = 0;
init(_filter2D, _rowFilter, _columnFilter, _srcType, _dstType, _bufType,
_rowBorderType, _columnBorderType, _borderValue);
}
@@ -566,7 +574,7 @@ struct RowVec_8u32s
struct SymmRowSmallVec_8u32s
{
SymmRowSmallVec_8u32s() { smallValues = false; }
SymmRowSmallVec_8u32s() { smallValues = false; symmetryType = 0; }
SymmRowSmallVec_8u32s( const Mat& _kernel, int _symmetryType )
{
kernel = _kernel;
@@ -870,7 +878,7 @@ struct SymmRowSmallVec_8u32s
struct SymmColumnVec_32s8u
{
SymmColumnVec_32s8u() { symmetryType=0; }
SymmColumnVec_32s8u() { symmetryType=0; delta = 0; }
SymmColumnVec_32s8u(const Mat& _kernel, int _symmetryType, int _bits, double _delta)
{
symmetryType = _symmetryType;
@@ -1018,7 +1026,7 @@ struct SymmColumnVec_32s8u
struct SymmColumnSmallVec_32s16s
{
SymmColumnSmallVec_32s16s() { symmetryType=0; }
SymmColumnSmallVec_32s16s() { symmetryType=0; delta = 0; }
SymmColumnSmallVec_32s16s(const Mat& _kernel, int _symmetryType, int _bits, double _delta)
{
symmetryType = _symmetryType;
@@ -1152,7 +1160,7 @@ struct SymmColumnSmallVec_32s16s
struct RowVec_16s32f
{
RowVec_16s32f() {}
RowVec_16s32f() { sse2_supported = false; }
RowVec_16s32f( const Mat& _kernel )
{
kernel = _kernel;
@@ -1199,7 +1207,7 @@ struct RowVec_16s32f
struct SymmColumnVec_32f16s
{
SymmColumnVec_32f16s() { symmetryType=0; }
SymmColumnVec_32f16s() { symmetryType=0; delta = 0; sse2_supported = false; }
SymmColumnVec_32f16s(const Mat& _kernel, int _symmetryType, int, double _delta)
{
symmetryType = _symmetryType;
@@ -1355,6 +1363,9 @@ struct RowVec_32f
{
haveSSE = checkHardwareSupport(CV_CPU_SSE);
haveAVX2 = checkHardwareSupport(CV_CPU_AVX2);
#if defined USE_IPP_SEP_FILTERS
bufsz = -1;
#endif
}
RowVec_32f( const Mat& _kernel )
@@ -1478,7 +1489,7 @@ private:
struct SymmRowSmallVec_32f
{
SymmRowSmallVec_32f() {}
SymmRowSmallVec_32f() { symmetryType = 0; }
SymmRowSmallVec_32f( const Mat& _kernel, int _symmetryType )
{
kernel = _kernel;
@@ -1675,6 +1686,7 @@ struct SymmColumnVec_32f
symmetryType=0;
haveSSE = checkHardwareSupport(CV_CPU_SSE);
haveAVX2 = checkHardwareSupport(CV_CPU_AVX2);
delta = 0;
}
SymmColumnVec_32f(const Mat& _kernel, int _symmetryType, int, double _delta)
{
@@ -1898,7 +1910,7 @@ if ( haveAVX2 )
struct SymmColumnSmallVec_32f
{
SymmColumnSmallVec_32f() { symmetryType=0; }
SymmColumnSmallVec_32f() { symmetryType=0; delta = 0; }
SymmColumnSmallVec_32f(const Mat& _kernel, int _symmetryType, int, double _delta)
{
symmetryType = _symmetryType;
@@ -2030,7 +2042,7 @@ struct SymmColumnSmallVec_32f
struct FilterVec_8u
{
FilterVec_8u() {}
FilterVec_8u() { delta = 0; _nz = 0; }
FilterVec_8u(const Mat& _kernel, int _bits, double _delta)
{
Mat kernel;
@@ -2113,7 +2125,7 @@ struct FilterVec_8u
struct FilterVec_8u16s
{
FilterVec_8u16s() {}
FilterVec_8u16s() { delta = 0; _nz = 0; }
FilterVec_8u16s(const Mat& _kernel, int _bits, double _delta)
{
Mat kernel;
@@ -2196,7 +2208,7 @@ struct FilterVec_8u16s
struct FilterVec_32f
{
FilterVec_32f() {}
FilterVec_32f() { delta = 0; _nz = 0; }
FilterVec_32f(const Mat& _kernel, int, double _delta)
{
delta = (float)_delta;
modules/imgproc/src/grabcut.cpp
+1
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@@ -104,6 +104,7 @@ GMM::GMM( Mat& _model )
for( int ci = 0; ci < componentsCount; ci++ )
if( coefs[ci] > 0 )
calcInverseCovAndDeterm( ci );
totalSampleCount = 0;
}
double GMM::operator()( const Vec3d color ) const
modules/imgproc/src/histogram.cpp
+5 -4
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@@ -1219,16 +1219,15 @@ public:
m_type = ippiGetDataType(src.type());
m_levelsNum = histSize+1;
ippiHistogram_C1 = getIppiHistogramFunction_C1(src.type());
m_fullRoi = ippiSize(src.size());
m_bufferSize = 0;
m_specSize = 0;
if(!ippiHistogram_C1)
{
ok = false;
return;
}
m_fullRoi = ippiSize(src.size());
m_bufferSize = 0;
m_specSize = 0;
if(ippiHistogramGetBufferSize(m_type, m_fullRoi, &m_levelsNum, 1, 1, &m_specSize, &m_bufferSize) < 0)
{
ok = false;
@@ -3530,6 +3529,8 @@ cvCalcArrBackProjectPatch( CvArr** arr, CvArr* dst, CvSize patch_size, CvHistogr
CV_Error( CV_StsBadSize, "The patch width and height must be positive" );
dims = cvGetDims( hist->bins );
if (dims < 1)
CV_Error( CV_StsOutOfRange, "Invalid number of dimensions");
cvNormalizeHist( hist, norm_factor );
for( i = 0; i < dims; i++ )
modules/imgproc/src/imgwarp.cpp
+3 -3
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@@ -6171,7 +6171,7 @@ static bool ocl_warpTransform_cols4(InputArray _src, OutputArray _dst, InputArra
_dst.create( dsize.area() == 0 ? src.size() : dsize, src.type() );
UMat dst = _dst.getUMat();
float M[9];
float M[9] = {0};
int matRows = (op_type == OCL_OP_AFFINE ? 2 : 3);
Mat matM(matRows, 3, CV_32F, M), M1 = _M0.getMat();
CV_Assert( (M1.type() == CV_32F || M1.type() == CV_64F) && M1.rows == matRows && M1.cols == 3 );
@@ -6269,7 +6269,7 @@ static bool ocl_warpTransform(InputArray _src, OutputArray _dst, InputArray _M0,
_dst.create( dsize.area() == 0 ? src.size() : dsize, src.type() );
UMat dst = _dst.getUMat();
double M[9];
double M[9] = {0};
int matRows = (op_type == OCL_OP_AFFINE ? 2 : 3);
Mat matM(matRows, 3, CV_64F, M), M1 = _M0.getMat();
CV_Assert( (M1.type() == CV_32F || M1.type() == CV_64F) &&
@@ -6364,7 +6364,7 @@ void cv::warpAffine( InputArray _src, OutputArray _dst,
if( dst.data == src.data )
src = src.clone();
double M[6];
double M[6] = {0};
Mat matM(2, 3, CV_64F, M);
if( interpolation == INTER_AREA )
interpolation = INTER_LINEAR;
modules/imgproc/src/lsd.cpp
+3 -2
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@@ -398,8 +398,9 @@ CV_EXPORTS Ptr<LineSegmentDetector> createLineSegmentDetector(
LineSegmentDetectorImpl::LineSegmentDetectorImpl(int _refine, double _scale, double _sigma_scale, double _quant,
double _ang_th, double _log_eps, double _density_th, int _n_bins)
:SCALE(_scale), doRefine(_refine), SIGMA_SCALE(_sigma_scale), QUANT(_quant),
ANG_TH(_ang_th), LOG_EPS(_log_eps), DENSITY_TH(_density_th), N_BINS(_n_bins)
: img_width(0), img_height(0), LOG_NT(0), w_needed(false), p_needed(false), n_needed(false),
SCALE(_scale), doRefine(_refine), SIGMA_SCALE(_sigma_scale), QUANT(_quant),
ANG_TH(_ang_th), LOG_EPS(_log_eps), DENSITY_TH(_density_th), N_BINS(_n_bins)
{
CV_Assert(_scale > 0 && _sigma_scale > 0 && _quant >= 0 &&
_ang_th > 0 && _ang_th < 180 && _density_th >= 0 && _density_th < 1 &&
modules/imgproc/src/samplers.cpp
+1 -1
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@@ -441,7 +441,7 @@ cvGetQuadrangleSubPix( const void* srcarr, void* dstarr, const CvMat* mat )
CV_Assert( src.channels() == dst.channels() );
cv::Size win_size = dst.size();
double matrix[6];
double matrix[6] = {0};
cv::Mat M(2, 3, CV_64F, matrix);
m.convertTo(M, CV_64F);
double dx = (win_size.width - 1)*0.5;
modules/imgproc/src/shapedescr.cpp
+1 -1
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@@ -359,7 +359,7 @@ cv::RotatedRect cv::fitEllipse( InputArray _points )
// New fitellipse algorithm, contributed by Dr. Daniel Weiss
Point2f c(0,0);
double gfp[5], rp[5], t;
double gfp[5] = {0}, rp[5] = {0}, t;
const double min_eps = 1e-8;
bool is_float = depth == CV_32F;
const Point* ptsi = points.ptr<Point>();