mirror/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2024-11-24 03:00:14 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

Fixed issues found by static analysis (mostly DBZ)

Browse Source
This commit is contained in:
Maksim Shabunin 2018-07-17 16:14:54 +03:00
parent 78d07e841d
commit 1da46fe6fb
26 changed files with 71 additions and 19 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
modules/calib3d/src/calibration.cpp
View File

@ -2336,10 +2336,13 @@ void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2,
_uu[2] = 1;
cvCrossProduct(&uu, &t, &ww);
nt = cvNorm(&t, 0, CV_L2);
CV_Assert(fabs(nt) > 0);
nw = cvNorm(&ww, 0, CV_L2);
CV_Assert(fabs(nw) > 0);
cvConvertScale(&ww, &ww, 1 / nw);
cvCrossProduct(&t, &ww, &w3);
nw = cvNorm(&w3, 0, CV_L2);
CV_Assert(fabs(nw) > 0);
cvConvertScale(&w3, &w3, 1 / nw);
_uu[2] = 0;
@ -3870,12 +3873,14 @@ float cv::rectify3Collinear( InputArray _cameraMatrix1, InputArray _distCoeffs1,
int idx = fabs(t12(0,0)) > fabs(t12(1,0)) ? 0 : 1;
double c = t12(idx,0), nt = norm(t12, CV_L2);
CV_Assert(fabs(nt) > 0);
Mat_<double> uu = Mat_<double>::zeros(3,1);
uu(idx, 0) = c > 0 ? 1 : -1;
// calculate global Z rotation
Mat_<double> ww = t12.cross(uu), wR;
double nw = norm(ww, CV_L2);
CV_Assert(fabs(nw) > 0);
ww *= acos(fabs(c)/nt)/nw;
Rodrigues(ww, wR);

1
modules/calib3d/src/dls.cpp
View File

@ -206,6 +206,7 @@ void dls::run_kernel(const cv::Mat& pp)
void dls::build_coeff_matrix(const cv::Mat& pp, cv::Mat& Mtilde, cv::Mat& D)
{
CV_Assert(!pp.empty());
cv::Mat eye = cv::Mat::eye(3, 3, CV_64F);
// build coeff matrix

12
modules/calib3d/src/fisheye.cpp
View File

@ -126,7 +126,8 @@ void cv::fisheye::projectPoints(InputArray objectPoints, OutputArray imagePoints
{
Vec3d Xi = objectPoints.depth() == CV_32F ? (Vec3d)Xf[i] : Xd[i];
Vec3d Y = aff*Xi;
if (fabs(Y[2]) < DBL_MIN)
Y[2] = 1;
Vec2d x(Y[0]/Y[2], Y[1]/Y[2]);
double r2 = x.dot(x);
@ -1186,6 +1187,7 @@ void cv::internal::ComputeExtrinsicRefine(const Mat& imagePoints, const Mat& obj
{
CV_Assert(!objectPoints.empty() && objectPoints.type() == CV_64FC3);
CV_Assert(!imagePoints.empty() && imagePoints.type() == CV_64FC2);
CV_Assert(rvec.total() > 2 && tvec.total() > 2);
Vec6d extrinsics(rvec.at<double>(0), rvec.at<double>(1), rvec.at<double>(2),
tvec.at<double>(0), tvec.at<double>(1), tvec.at<double>(2));
double change = 1;
@ -1365,9 +1367,13 @@ void cv::internal::InitExtrinsics(const Mat& _imagePoints, const Mat& _objectPoi
double sc = .5 * (norm(H.col(0)) + norm(H.col(1)));
H = H / sc;
Mat u1 = H.col(0).clone();
u1 = u1 / norm(u1);
double norm_u1 = norm(u1);
CV_Assert(fabs(norm_u1) > 0);
u1 = u1 / norm_u1;
Mat u2 = H.col(1).clone() - u1.dot(H.col(1).clone()) * u1;
u2 = u2 / norm(u2);
double norm_u2 = norm(u2);
CV_Assert(fabs(norm_u2) > 0);
u2 = u2 / norm_u2;
Mat u3 = u1.cross(u2);
Mat RRR;
hconcat(u1, u2, RRR);

1
modules/calib3d/src/homography_decomp.cpp
View File

@ -194,6 +194,7 @@ void HomographyDecompZhang::decompose(std::vector<CameraMotion>& camMotions)
{
Mat W, U, Vt;
SVD::compute(getHnorm(), W, U, Vt);
CV_Assert(W.total() > 2 && Vt.total() > 7);
double lambda1=W.at<double>(0);
double lambda3=W.at<double>(2);
double lambda1m3 = (lambda1-lambda3);

8
modules/core/include/opencv2/core/mat.inl.hpp
View File

@ -861,7 +861,9 @@ bool Mat::isSubmatrix() const
inline
size_t Mat::elemSize() const
{
return dims > 0 ? step.p[dims - 1] : 0;
size_t res = dims > 0 ? step.p[dims - 1] : 0;
CV_DbgAssert(res != 0);
return res;
}
inline
@ -3789,7 +3791,9 @@ bool UMat::isSubmatrix() const
inline
size_t UMat::elemSize() const
{
return dims > 0 ? step.p[dims - 1] : 0;
size_t res = dims > 0 ? step.p[dims - 1] : 0;
CV_DbgAssert(res != 0);
return res;
}
inline

1
modules/core/src/batch_distance.cpp
View File

@ -263,6 +263,7 @@ void cv::batchDistance( InputArray _src1, InputArray _src2,
if( crosscheck )
{
CV_Assert( K == 1 && update == 0 && mask.empty() );
CV_Assert(!nidx.empty());
Mat tdist, tidx;
batchDistance(src2, src1, tdist, dtype, tidx, normType, K, mask, 0, false);

2
modules/dnn/src/layers/resize_layer.cpp
View File

@ -14,7 +14,7 @@ namespace cv { namespace dnn {
class ResizeLayerImpl : public ResizeLayer
{
public:
ResizeLayerImpl(const LayerParams& params)
ResizeLayerImpl(const LayerParams& params) : scaleWidth(0), scaleHeight(0)
{
setParamsFrom(params);
outWidth = params.get<float>("width", 0);

1
modules/features2d/src/bagofwords.cpp
View File

@ -177,6 +177,7 @@ void BOWImgDescriptorExtractor::compute( InputArray keypointDescriptors, OutputA
CV_INSTRUMENT_REGION()
CV_Assert( !vocabulary.empty() );
CV_Assert(!keypointDescriptors.empty());
int clusterCount = descriptorSize(); // = vocabulary.rows

3
modules/features2d/src/blobdetector.cpp
View File

@ -264,6 +264,8 @@ void SimpleBlobDetectorImpl::findBlobs(InputArray _image, InputArray _binaryImag
convexHull(Mat(contours[contourIdx]), hull);
double area = contourArea(Mat(contours[contourIdx]));
double hullArea = contourArea(Mat(hull));
if (fabs(hullArea) < DBL_EPSILON)
continue;
double ratio = area / hullArea;
if (ratio < params.minConvexity || ratio >= params.maxConvexity)
continue;
@ -309,6 +311,7 @@ void SimpleBlobDetectorImpl::detect(InputArray image, std::vector<cv::KeyPoint>&
CV_INSTRUMENT_REGION()
keypoints.clear();
CV_Assert(params.minRepeatability != 0);
Mat grayscaleImage;
if (image.channels() == 3 || image.channels() == 4)
cvtColor(image, grayscaleImage, COLOR_BGR2GRAY);

2
modules/features2d/src/brisk.cpp
View File

@ -506,6 +506,7 @@ BRISK_Impl::smoothedIntensity(const cv::Mat& image, const cv::Mat& integral, con
// scaling:
const int scaling = (int)(4194304.0 / area);
const int scaling2 = int(float(scaling) * area / 1024.0);
CV_Assert(scaling2 != 0);
// the integral image is larger:
const int integralcols = imagecols + 1;
@ -2238,6 +2239,7 @@ BriskLayer::value(const cv::Mat& mat, float xf, float yf, float scale_in) const
// scaling:
const int scaling = (int)(4194304.0f / area);
const int scaling2 = (int)(float(scaling) * area / 1024.0f);
CV_Assert(scaling2 != 0);
// calculate borders
const float x_1 = xf - sigma_half;

2
modules/imgproc/src/deriv.cpp
View File

@ -546,10 +546,10 @@ static bool ocl_Laplacian5(InputArray _src, OutputArray _dst,
size_t lmsz = dev.localMemSize();
size_t src_step = _src.step(), src_offset = _src.offset();
const size_t tileSizeYmax = wgs / tileSizeX;
CV_Assert(src_step != 0 && esz != 0);
// workaround for NVIDIA: 3 channel vector type takes 4*elem_size in local memory
int loc_mem_cn = dev.vendorID() == ocl::Device::VENDOR_NVIDIA && cn == 3 ? 4 : cn;
if (((src_offset % src_step) % esz == 0) &&
(
(borderType == BORDER_CONSTANT || borderType == BORDER_REPLICATE) ||

12
modules/imgproc/src/filter.cpp
View File

@ -4284,10 +4284,14 @@ static bool ocl_sepFilter2D_SinglePass(InputArray _src, OutputArray _dst,
size_t src_step = _src.step(), src_offset = _src.offset();
bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
if ((src_offset % src_step) % esz != 0 || (!doubleSupport && (sdepth == CV_64F || ddepth == CV_64F)) ||
!(borderType == BORDER_CONSTANT || borderType == BORDER_REPLICATE ||
borderType == BORDER_REFLECT || borderType == BORDER_WRAP ||
borderType == BORDER_REFLECT_101))
if (esz == 0
|| (src_offset % src_step) % esz != 0
|| (!doubleSupport && (sdepth == CV_64F || ddepth == CV_64F))
|| !(borderType == BORDER_CONSTANT
|| borderType == BORDER_REPLICATE
|| borderType == BORDER_REFLECT
|| borderType == BORDER_WRAP
|| borderType == BORDER_REFLECT_101))
return false;
size_t lt2[2] = { optimizedSepFilterLocalWidth, optimizedSepFilterLocalHeight };

1
modules/imgproc/src/grabcut.cpp
View File

@ -174,6 +174,7 @@ void GMM::addSample( int ci, const Vec3d color )
void GMM::endLearning()
{
CV_Assert(totalSampleCount > 0);
const double variance = 0.01;
for( int ci = 0; ci < componentsCount; ci++ )
{

2
modules/imgproc/src/imgwarp.cpp
View File

@ -3286,6 +3286,7 @@ void cv::warpPolar(InputArray _src, OutputArray _dst, Size dsize,
if (!(flags & CV_WARP_INVERSE_MAP))
{
CV_Assert(!dsize.empty());
double Kangle = CV_2PI / dsize.height;
int phi, rho;
@ -3332,6 +3333,7 @@ void cv::warpPolar(InputArray _src, OutputArray _dst, Size dsize,
Mat src = _dst.getMat();
Size ssize = _dst.size();
ssize.height -= 2 * ANGLE_BORDER;
CV_Assert(!ssize.empty());
const double Kangle = CV_2PI / ssize.height;
double Kmag;
if (semiLog)

2
modules/imgproc/src/linefit.cpp
View File

@ -47,6 +47,7 @@ static const double eps = 1e-6;
static void fitLine2D_wods( const Point2f* points, int count, float *weights, float *line )
{
CV_Assert(count > 0);
double x = 0, y = 0, x2 = 0, y2 = 0, xy = 0, w = 0;
double dx2, dy2, dxy;
int i;
@ -98,6 +99,7 @@ static void fitLine2D_wods( const Point2f* points, int count, float *weights, fl
static void fitLine3D_wods( const Point3f * points, int count, float *weights, float *line )
{
CV_Assert(count > 0);
int i;
float w0 = 0;
float x0 = 0, y0 = 0, z0 = 0;

1
modules/imgproc/src/lsd.cpp
View File

@ -772,6 +772,7 @@ bool LineSegmentDetectorImpl::refine(std::vector<RegionPoint>& reg, double reg_a
++n;
}
}
CV_Assert(n > 0);
double mean_angle = sum / double(n);
// 2 * standard deviation
double tau = 2.0 * sqrt((s_sum - 2.0 * mean_angle * sum) / double(n) + mean_angle * mean_angle);

11
modules/imgproc/src/moments.cpp
View File

@ -495,6 +495,13 @@ static bool ocl_moments( InputArray _src, Moments& m, bool binary)
const int TILE_SIZE = 32;
const int K = 10;
Size sz = _src.getSz();
int xtiles = divUp(sz.width, TILE_SIZE);
int ytiles = divUp(sz.height, TILE_SIZE);
int ntiles = xtiles*ytiles;
if (ntiles == 0)
return false;
ocl::Kernel k = ocl::Kernel("moments", ocl::imgproc::moments_oclsrc,
format("-D TILE_SIZE=%d%s",
TILE_SIZE,
@ -504,10 +511,6 @@ static bool ocl_moments( InputArray _src, Moments& m, bool binary)
return false;
UMat src = _src.getUMat();
Size sz = src.size();
int xtiles = (sz.width + TILE_SIZE-1)/TILE_SIZE;
int ytiles = (sz.height + TILE_SIZE-1)/TILE_SIZE;
int ntiles = xtiles*ytiles;
UMat umbuf(1, ntiles*K, CV_32S);
size_t globalsize[] = {(size_t)xtiles, std::max((size_t)TILE_SIZE, (size_t)sz.height)};

6
modules/imgproc/src/smooth.cpp
View File

@ -1709,6 +1709,7 @@ void cv::sqrBoxFilter( InputArray _src, OutputArray _dst, int ddepth,
cv::Mat cv::getGaussianKernel( int n, double sigma, int ktype )
{
CV_Assert(n > 0);
const int SMALL_GAUSSIAN_SIZE = 7;
static const float small_gaussian_tab[][SMALL_GAUSSIAN_SIZE] =
{
@ -1747,6 +1748,7 @@ cv::Mat cv::getGaussianKernel( int n, double sigma, int ktype )
}
}
CV_DbgAssert(fabs(sum) > 0);
sum = 1./sum;
for( i = 0; i < n; i++ )
{
@ -5334,6 +5336,7 @@ public:
wsum += w;
}
// overflow is not possible here => there is no need to use cv::saturate_cast
CV_DbgAssert(fabs(wsum) > 0);
dptr[j] = (uchar)cvRound(sum/wsum);
}
}
@ -5419,6 +5422,7 @@ public:
sum_b += b*w; sum_g += g*w; sum_r += r*w;
wsum += w;
}
CV_DbgAssert(fabs(wsum) > 0);
wsum = 1.f/wsum;
b0 = cvRound(sum_b*wsum);
g0 = cvRound(sum_g*wsum);
@ -5678,6 +5682,7 @@ public:
sum += val*w;
wsum += w;
}
CV_DbgAssert(fabs(wsum) > 0);
dptr[j] = (float)(sum/wsum);
}
}
@ -5768,6 +5773,7 @@ public:
sum_b += b*w; sum_g += g*w; sum_r += r*w;
wsum += w;
}
CV_DbgAssert(fabs(wsum) > 0);
wsum = 1.f/wsum;
b0 = sum_b*wsum;
g0 = sum_g*wsum;

1
modules/ml/src/em.cpp
View File

@ -616,6 +616,7 @@ public:
expDiffSum += v; // sum_j(exp(L_ij - L_iq))
}
CV_Assert(expDiffSum > 0);
if(probs)
L.convertTo(*probs, ptype, 1./expDiffSum);

1
modules/ml/src/rtrees.cpp
View File

@ -170,6 +170,7 @@ public:
double val = std::abs(w->ord_responses[w->sidx[i]]);
max_response = std::max(max_response, val);
}
CV_Assert(fabs(max_response) > 0);
}
if( rparams.calcVarImportance )

2
modules/ml/src/tree.cpp
View File

@ -630,7 +630,7 @@ void DTreesImpl::calcValue( int nidx, const vector<int>& _sidx )
w->cv_Tn[nidx*cv_n + j] = INT_MAX;
}
}
CV_Assert(fabs(sumw) > 0);
node->node_risk = sum2 - (sum/sumw)*sum;
node->node_risk /= sumw;
node->value = sum/sumw;

2
modules/objdetect/src/haar.cpp
View File

@ -599,7 +599,7 @@ cvSetImagesForHaarClassifierCascade( CvHaarClassifierCascade* _cascade,
else
sum0 += hidfeature->rect[k].weight * tr.width * tr.height;
}
CV_Assert(area0 > 0);
hidfeature->rect[0].weight = (float)(-sum0/area0);
} /* l */
} /* j */

2
modules/objdetect/src/qrcode.cpp
View File

@ -111,6 +111,7 @@ vector<Vec3d> QRDecode::searchVerticalLines()
for (size_t i = 0; i < test_lines.size(); i++) { length += test_lines[i]; }
CV_Assert(length > 0);
for (size_t i = 0; i < test_lines.size(); i++)
{
if (i == 2) { weight += abs((test_lines[i] / length) - 3.0/7.0); }
@ -182,6 +183,7 @@ vector<Point2f> QRDecode::separateHorizontalLines(vector<Vec3d> list_lines)
for (size_t i = 0; i < test_lines.size(); i++) { length += test_lines[i]; }
CV_Assert(length > 0);
for (size_t i = 0; i < test_lines.size(); i++)
{
if (i % 3 == 0) { weight += abs((test_lines[i] / length) - 3.0/14.0); }

6
modules/photo/src/tonemap.cpp
View File

@ -140,6 +140,7 @@ public:
double max;
minMaxLoc(gray_img, NULL, &max);
CV_Assert(max > 0);
Mat map;
log(gray_img + 1.0f, map);
@ -429,12 +430,15 @@ public:
for(int i = 0; i < max_iterations; i++)
{
calculateProduct(p, product);
float alpha = rr / static_cast<float>(p.dot(product));
double dprod = p.dot(product);
CV_Assert(fabs(dprod) > 0);
float alpha = rr / static_cast<float>(dprod);
r -= alpha * product;
x += alpha * p;
float new_rr = static_cast<float>(r.dot(r));
CV_Assert(fabs(rr) > 0);
p = r + (new_rr / rr) * p;
rr = new_rr;

1
modules/shape/src/sc_dis.cpp
View File

@ -743,6 +743,7 @@ void SCDMatcher::hungarian(cv::Mat &costMatrix, std::vector<cv::DMatch> &outMatc
// calculate symmetric shape context cost
cv::Mat trueCostMatrix(costMatrix, cv::Rect(0,0,sizeScd1, sizeScd2));
CV_Assert(!trueCostMatrix.empty());
float leftcost = 0;
for (int nrow=0; nrow<trueCostMatrix.rows; nrow++)
{

2
modules/videostab/src/inpainting.cpp
View File

@ -447,7 +447,7 @@ public:
}
}
float wSumInv = 1.f / wSum;
float wSumInv = (std::fabs(wSum) > 0) ? (1.f / wSum) : 0; // if wSum is 0, c1-c3 will be 0 too
frame(y,x) = Point3_<uchar>(
static_cast<uchar>(c1*wSumInv),
static_cast<uchar>(c2*wSumInv),