cppcheck: fix some reports

All of these: (performance) Prefer prefix ++/-- operators for non-primitive types.
[modules/calib3d/src/fundam.cpp:1049] -> [modules/calib3d/src/fundam.cpp:1049]: (style) Same expression on both sides of '&&'.
pull/6489/head
Julien Nabet 9 years ago
parent 6e5e5d87df
commit a29c814bd8
  1. 6
      apps/traincascade/cascadeclassifier.cpp
  2. 20
      modules/calib3d/src/circlesgrid.cpp
  3. 2
      modules/calib3d/src/fundam.cpp
  4. 2
      modules/core/src/matmul.cpp
  5. 4
      modules/cudalegacy/test/NCVTest.hpp
  6. 4
      modules/features2d/src/agast.cpp
  7. 4
      modules/ts/src/ocl_test.cpp
  8. 2
      modules/videoio/src/cap_gphoto2.cpp
  9. 6
      samples/cpp/detect_blob.cpp
  10. 10
      samples/cpp/detect_mser.cpp
  11. 2
      samples/cpp/facedetect.cpp
  12. 12
      samples/cpp/matchmethod_orb_akaze_brisk.cpp
  13. 2
      samples/cpp/smiledetect.cpp
  14. 2
      samples/tapi/ufacedetect.cpp

@ -290,7 +290,7 @@ int CvCascadeClassifier::predict( int sampleIdx )
{
CV_DbgAssert( sampleIdx < numPos + numNeg );
for (vector< Ptr<CvCascadeBoost> >::iterator it = stageClassifiers.begin();
it != stageClassifiers.end(); it++ )
it != stageClassifiers.end();++it )
{
if ( (*it)->predict( sampleIdx ) == 0.f )
return 0;
@ -365,7 +365,7 @@ void CvCascadeClassifier::writeStages( FileStorage &fs, const Mat& featureMap )
int i = 0;
fs << CC_STAGES << "[";
for( vector< Ptr<CvCascadeBoost> >::const_iterator it = stageClassifiers.begin();
it != stageClassifiers.end(); it++, i++ )
it != stageClassifiers.end();++it, ++i )
{
sprintf( cmnt, "stage %d", i );
cvWriteComment( fs.fs, cmnt, 0 );
@ -557,7 +557,7 @@ void CvCascadeClassifier::getUsedFeaturesIdxMap( Mat& featureMap )
featureMap.setTo(Scalar(-1));
for( vector< Ptr<CvCascadeBoost> >::const_iterator it = stageClassifiers.begin();
it != stageClassifiers.end(); it++ )
it != stageClassifiers.end();++it )
(*it)->markUsedFeaturesInMap( featureMap );
for( int fi = 0, idx = 0; fi < varCount; fi++ )

@ -129,7 +129,7 @@ void CirclesGridClusterFinder::hierarchicalClustering(const std::vector<Point2f>
}
patternPoints.reserve(clusters[patternClusterIdx].size());
for(std::list<size_t>::iterator it = clusters[patternClusterIdx].begin(); it != clusters[patternClusterIdx].end(); it++)
for(std::list<size_t>::iterator it = clusters[patternClusterIdx].begin(); it != clusters[patternClusterIdx].end();++it)
{
patternPoints.push_back(points[*it]);
}
@ -320,7 +320,7 @@ void CirclesGridClusterFinder::getSortedCorners(const std::vector<cv::Point2f> &
std::vector<Point2f>::const_iterator firstCornerIterator = std::find(hull2f.begin(), hull2f.end(), firstCorner);
sortedCorners.clear();
for(std::vector<Point2f>::const_iterator it = firstCornerIterator; it != hull2f.end(); it++)
for(std::vector<Point2f>::const_iterator it = firstCornerIterator; it != hull2f.end();++it)
{
std::vector<Point2f>::const_iterator itCorners = std::find(corners.begin(), corners.end(), *it);
if(itCorners != corners.end())
@ -328,7 +328,7 @@ void CirclesGridClusterFinder::getSortedCorners(const std::vector<cv::Point2f> &
sortedCorners.push_back(*it);
}
}
for(std::vector<Point2f>::const_iterator it = hull2f.begin(); it != firstCornerIterator; it++)
for(std::vector<Point2f>::const_iterator it = hull2f.begin(); it != firstCornerIterator;++it)
{
std::vector<Point2f>::const_iterator itCorners = std::find(corners.begin(), corners.end(), *it);
if(itCorners != corners.end())
@ -493,21 +493,21 @@ void Graph::floydWarshall(cv::Mat &distanceMatrix, int infinity) const
const int n = (int)getVerticesCount();
distanceMatrix.create(n, n, CV_32SC1);
distanceMatrix.setTo(infinity);
for (Vertices::const_iterator it1 = vertices.begin(); it1 != vertices.end(); it1++)
for (Vertices::const_iterator it1 = vertices.begin(); it1 != vertices.end();++it1)
{
distanceMatrix.at<int> ((int)it1->first, (int)it1->first) = 0;
for (Neighbors::const_iterator it2 = it1->second.neighbors.begin(); it2 != it1->second.neighbors.end(); it2++)
for (Neighbors::const_iterator it2 = it1->second.neighbors.begin(); it2 != it1->second.neighbors.end();++it2)
{
CV_Assert( it1->first != *it2 );
distanceMatrix.at<int> ((int)it1->first, (int)*it2) = edgeWeight;
}
}
for (Vertices::const_iterator it1 = vertices.begin(); it1 != vertices.end(); it1++)
for (Vertices::const_iterator it1 = vertices.begin(); it1 != vertices.end();++it1)
{
for (Vertices::const_iterator it2 = vertices.begin(); it2 != vertices.end(); it2++)
for (Vertices::const_iterator it2 = vertices.begin(); it2 != vertices.end();++it2)
{
for (Vertices::const_iterator it3 = vertices.begin(); it3 != vertices.end(); it3++)
for (Vertices::const_iterator it3 = vertices.begin(); it3 != vertices.end();++it3)
{
int i1 = (int)it1->first, i2 = (int)it2->first, i3 = (int)it3->first;
int val1 = distanceMatrix.at<int> (i2, i3);
@ -618,10 +618,10 @@ void CirclesGridFinder::rng2gridGraph(Graph &rng, std::vector<cv::Point2f> &vect
for (size_t i = 0; i < rng.getVerticesCount(); i++)
{
Graph::Neighbors neighbors1 = rng.getNeighbors(i);
for (Graph::Neighbors::iterator it1 = neighbors1.begin(); it1 != neighbors1.end(); it1++)
for (Graph::Neighbors::iterator it1 = neighbors1.begin(); it1 != neighbors1.end(); ++it1)
{
Graph::Neighbors neighbors2 = rng.getNeighbors(*it1);
for (Graph::Neighbors::iterator it2 = neighbors2.begin(); it2 != neighbors2.end(); it2++)
for (Graph::Neighbors::iterator it2 = neighbors2.begin(); it2 != neighbors2.end(); ++it2)
{
if (i < *it2)
{

@ -1046,7 +1046,7 @@ void cv::convertPointsHomogeneous( InputArray _src, OutputArray _dst )
}
double cv::sampsonDistance(InputArray _pt1, InputArray _pt2, InputArray _F) {
CV_Assert(_pt1.type() == CV_64F && _pt1.type() == CV_64F && _F.type() == CV_64F);
CV_Assert(_pt1.type() == CV_64F && _pt2.type() == CV_64F && _F.type() == CV_64F);
CV_DbgAssert(_pt1.rows() == 3 && _F.size() == Size(3, 3) && _pt1.rows() == _pt2.rows());
Mat pt1(_pt1.getMat());

@ -2414,7 +2414,7 @@ void cv::calcCovarMatrix( InputArray _src, OutputArray _covar, InputOutputArray
Mat _data(static_cast<int>(src.size()), size.area(), type);
int i = 0;
for(std::vector<cv::Mat>::iterator each = src.begin(); each != src.end(); each++, i++ )
for(std::vector<cv::Mat>::iterator each = src.begin(); each != src.end(); ++each, ++i )
{
CV_Assert( (*each).size() == size && (*each).type() == type );
Mat dataRow(size.height, size.width, type, _data.ptr(i));

@ -214,12 +214,12 @@ private:
stream << "====================================================" << std::endl << std::endl;
stream << "Test initialization report: " << std::endl;
for (std::map<std::string,std::string>::iterator it=report.statsText.begin();
it != report.statsText.end(); it++)
it != report.statsText.end(); ++it)
{
stream << it->first << "=" << it->second << std::endl;
}
for (std::map<std::string,Ncv32u>::iterator it=report.statsNums.begin();
it != report.statsNums.end(); it++)
it != report.statsNums.end(); ++it)
{
stream << it->first << "=" << it->second << std::endl;
}

@ -8033,7 +8033,7 @@ void AGAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, boo
makeAgastOffsets(pixel_, (int)img.step, type);
std::vector<KeyPoint>::iterator kpt;
for(kpt = kpts.begin(); kpt != kpts.end(); kpt++)
for(kpt = kpts.begin(); kpt != kpts.end(); ++kpt)
{
switch(type) {
case AgastFeatureDetector::AGAST_5_8:
@ -8149,7 +8149,7 @@ void AGAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, boo
}
}
}
currCorner++;
++currCorner;
}
// collecting maximum corners

@ -267,7 +267,7 @@ double TestUtils::checkRectSimilarity(const Size & sz, std::vector<Rect>& ob1, s
cv::Mat cpu_result(sz, CV_8UC1);
cpu_result.setTo(0);
for (vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
for (vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); ++r)
{
cv::Mat cpu_result_roi(cpu_result, *r);
cpu_result_roi.setTo(1);
@ -277,7 +277,7 @@ double TestUtils::checkRectSimilarity(const Size & sz, std::vector<Rect>& ob1, s
cv::Mat gpu_result(sz, CV_8UC1);
gpu_result.setTo(0);
for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); ++r2)
{
cv::Mat gpu_result_roi(gpu_result, *r2);
gpu_result_roi.setTo(1);

@ -981,7 +981,7 @@ CameraWidget * DigitalCameraCapture::findWidgetByName(
CR(gp_widget_get_name(it->second, &name));
if (strstr(name, subName))
break;
it++;
++it;
}
return (it != end) ? it->second : NULL;
}

@ -159,14 +159,14 @@ int main(int argc, char *argv[])
String label;
// Descriptor loop
vector<String>::iterator itDesc;
for (itDesc = typeDesc.begin(); itDesc != typeDesc.end(); itDesc++)
for (itDesc = typeDesc.begin(); itDesc != typeDesc.end(); ++itDesc)
{
vector<KeyPoint> keyImg1;
if (*itDesc == "BLOB")
{
b = SimpleBlobDetector::create(*itBLOB);
label = Legende(*itBLOB);
itBLOB++;
++itBLOB;
}
try
{
@ -181,7 +181,7 @@ int main(int argc, char *argv[])
sbd->detect(img, keyImg, Mat());
drawKeypoints(img, keyImg, result);
int i = 0;
for (vector<KeyPoint>::iterator k = keyImg.begin(); k != keyImg.end(); k++, i++)
for (vector<KeyPoint>::iterator k = keyImg.begin(); k != keyImg.end(); ++k, ++i)
circle(result, k->pt, (int)k->size, palette[i % 65536]);
}
namedWindow(*itDesc + label, WINDOW_AUTOSIZE);

@ -466,7 +466,7 @@ int main(int argc, char *argv[])
// Descriptor loop
vector<String>::iterator itDesc;
Mat result(img.rows, img.cols, CV_8UC3);
for (itDesc = typeDesc.begin(); itDesc != typeDesc.end(); itDesc++)
for (itDesc = typeDesc.begin(); itDesc != typeDesc.end(); ++itDesc)
{
vector<KeyPoint> keyImg1;
if (*itDesc == "MSER"){
@ -475,7 +475,7 @@ int main(int argc, char *argv[])
b = MSER::create(itMSER->delta, itMSER->minArea, itMSER->maxArea, itMSER->maxVariation, itMSER->minDiversity, itMSER->maxEvolution,
itMSER->areaThreshold, itMSER->minMargin, itMSER->edgeBlurSize);
label = Legende(*itMSER);
itMSER++;
++itMSER;
}
else
@ -483,7 +483,7 @@ int main(int argc, char *argv[])
b = MSER::create(itMSER->delta, itMSER->minArea, itMSER->maxArea, itMSER->maxVariation, itMSER->minDiversity);
b.dynamicCast<MSER>()->setPass2Only(itMSER->pass2Only);
label = Legende(*itMSER);
itMSER++;
++itMSER;
}
}
if (img.type()==CV_8UC3)
@ -513,9 +513,9 @@ int main(int argc, char *argv[])
int i = 0;
//result = Scalar(0, 0, 0);
int nbPixelInMSER=0;
for (vector<vector <Point> >::iterator itr = region.begin(); itr != region.end(); itr++, i++)
for (vector<vector <Point> >::iterator itr = region.begin(); itr != region.end(); ++itr, ++i)
{
for (vector <Point>::iterator itp = region[i].begin(); itp != region[i].end(); itp ++)
for (vector <Point>::iterator itp = region[i].begin(); itp != region[i].end(); ++itp)
{
// all pixels belonging to region become blue
result.at<Vec3b>(itp->y, itp->x) = Vec3b(128, 0, 0);

@ -193,7 +193,7 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
//|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE,
Size(30, 30) );
for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ )
for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); ++r )
{
faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
}

@ -59,7 +59,7 @@ int main(int argc, char *argv[])
// Descriptor loop
vector<String>::iterator itDesc;
for (itDesc = typeDesc.begin(); itDesc != typeDesc.end(); itDesc++)
for (itDesc = typeDesc.begin(); itDesc != typeDesc.end(); ++itDesc)
{
Ptr<DescriptorMatcher> descriptorMatcher;
// Match between img1 and img2
@ -90,7 +90,7 @@ int main(int argc, char *argv[])
// or detect and compute descriptors in one step
b->detectAndCompute(img2, Mat(),keyImg2, descImg2,false);
// Match method loop
for (itMatcher = typeAlgoMatch.begin(); itMatcher != typeAlgoMatch.end(); itMatcher++){
for (itMatcher = typeAlgoMatch.begin(); itMatcher != typeAlgoMatch.end(); ++itMatcher){
descriptorMatcher = DescriptorMatcher::create(*itMatcher);
if ((*itMatcher == "BruteForce-Hamming" || *itMatcher == "BruteForce-Hamming(2)") && (b->descriptorType() == CV_32F || b->defaultNorm() <= NORM_L2SQR))
{
@ -135,7 +135,7 @@ int main(int argc, char *argv[])
cout << "in img1\tin img2\n";
// Use to compute distance between keyPoint matches and to evaluate match algorithm
double cumSumDist2=0;
for (it = bestMatches.begin(); it != bestMatches.end(); it++)
for (it = bestMatches.begin(); it != bestMatches.end(); ++it)
{
cout << it->queryIdx << "\t" << it->trainIdx << "\t" << it->distance << "\n";
Point2d p=keyImg1[it->queryIdx].pt-keyImg2[it->trainIdx].pt;
@ -165,15 +165,15 @@ int main(int argc, char *argv[])
int i=0;
cout << "Cumulative distance between keypoint match for different algorithm and feature detector \n\t";
cout << "We cannot say which is the best but we can say results are differents! \n\t";
for (vector<String>::iterator itMatcher = typeAlgoMatch.begin(); itMatcher != typeAlgoMatch.end(); itMatcher++)
for (vector<String>::iterator itMatcher = typeAlgoMatch.begin(); itMatcher != typeAlgoMatch.end(); ++itMatcher)
{
cout<<*itMatcher<<"\t";
}
cout << "\n";
for (itDesc = typeDesc.begin(); itDesc != typeDesc.end(); itDesc++)
for (itDesc = typeDesc.begin(); itDesc != typeDesc.end(); ++itDesc)
{
cout << *itDesc << "\t";
for (vector<String>::iterator itMatcher = typeAlgoMatch.begin(); itMatcher != typeAlgoMatch.end(); itMatcher++, i++)
for (vector<String>::iterator itMatcher = typeAlgoMatch.begin(); itMatcher != typeAlgoMatch.end(); ++itMatcher, ++i)
{
cout << desMethCmp[i]<<"\t";
}

@ -153,7 +153,7 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
//|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE,
Size(30, 30) );
for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ )
for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); ++r )
{
faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
}

@ -195,7 +195,7 @@ void detectAndDraw( UMat& img, Mat& canvas, CascadeClassifier& cascade,
//|CASCADE_DO_ROUGH_SEARCH
|CASCADE_SCALE_IMAGE,
Size(30, 30) );
for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ )
for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); ++r )
{
faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
}

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