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Remove all using directives for STL namespace and members

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Made all STL usages explicit to be able automatically find all usages of
particular class or function.
This commit is contained in:
Andrey Kamaev
2013-02-24 20:14:01 +04:00
parent f783f34e0b
commit 2a6fb2867e
310 changed files with 5744 additions and 5964 deletions
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modules/features2d/src/detectors.cpp
+18 -20
View File
@@ -41,8 +41,6 @@
#include "precomp.hpp"
using namespace std;
namespace cv
{
@@ -53,7 +51,7 @@ namespace cv
FeatureDetector::~FeatureDetector()
{}
void FeatureDetector::detect( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask ) const
void FeatureDetector::detect( const Mat& image, std::vector<KeyPoint>& keypoints, const Mat& mask ) const
{
keypoints.clear();
@@ -65,7 +63,7 @@ void FeatureDetector::detect( const Mat& image, vector<KeyPoint>& keypoints, con
detectImpl( image, keypoints, mask );
}
void FeatureDetector::detect(const vector<Mat>& imageCollection, vector<vector<KeyPoint> >& pointCollection, const vector<Mat>& masks ) const
void FeatureDetector::detect(const std::vector<Mat>& imageCollection, std::vector<std::vector<KeyPoint> >& pointCollection, const std::vector<Mat>& masks ) const
{
pointCollection.resize( imageCollection.size() );
for( size_t i = 0; i < imageCollection.size(); i++ )
@@ -83,12 +81,12 @@ bool FeatureDetector::empty() const
return false;
}
void FeatureDetector::removeInvalidPoints( const Mat& mask, vector<KeyPoint>& keypoints )
void FeatureDetector::removeInvalidPoints( const Mat& mask, std::vector<KeyPoint>& keypoints )
{
KeyPointsFilter::runByPixelsMask( keypoints, mask );
}
Ptr<FeatureDetector> FeatureDetector::create( const string& detectorType )
Ptr<FeatureDetector> FeatureDetector::create( const std::string& detectorType )
{
if( detectorType.find("Grid") == 0 )
{
@@ -127,17 +125,17 @@ GFTTDetector::GFTTDetector( int _nfeatures, double _qualityLevel,
{
}
void GFTTDetector::detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask) const
void GFTTDetector::detectImpl( const Mat& image, std::vector<KeyPoint>& keypoints, const Mat& mask) const
{
Mat grayImage = image;
if( image.type() != CV_8U ) cvtColor( image, grayImage, CV_BGR2GRAY );
vector<Point2f> corners;
std::vector<Point2f> corners;
goodFeaturesToTrack( grayImage, corners, nfeatures, qualityLevel, minDistance, mask,
blockSize, useHarrisDetector, k );
keypoints.resize(corners.size());
vector<Point2f>::const_iterator corner_it = corners.begin();
vector<KeyPoint>::iterator keypoint_it = keypoints.begin();
std::vector<Point2f>::const_iterator corner_it = corners.begin();
std::vector<KeyPoint>::iterator keypoint_it = keypoints.begin();
for( ; corner_it != corners.end(); ++corner_it, ++keypoint_it )
{
*keypoint_it = KeyPoint( *corner_it, (float)blockSize );
@@ -159,7 +157,7 @@ DenseFeatureDetector::DenseFeatureDetector( float _initFeatureScale, int _featur
{}
void DenseFeatureDetector::detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask ) const
void DenseFeatureDetector::detectImpl( const Mat& image, std::vector<KeyPoint>& keypoints, const Mat& mask ) const
{
float curScale = static_cast<float>(initFeatureScale);
int curStep = initXyStep;
@@ -203,11 +201,11 @@ struct ResponseComparator
}
};
static void keepStrongest( int N, vector<KeyPoint>& keypoints )
static void keepStrongest( int N, std::vector<KeyPoint>& keypoints )
{
if( (int)keypoints.size() > N )
{
vector<KeyPoint>::iterator nth = keypoints.begin() + N;
std::vector<KeyPoint>::iterator nth = keypoints.begin() + N;
std::nth_element( keypoints.begin(), nth, keypoints.end(), ResponseComparator() );
keypoints.erase( nth, keypoints.end() );
}
@@ -219,7 +217,7 @@ class GridAdaptedFeatureDetectorInvoker
private:
int gridRows_, gridCols_;
int maxPerCell_;
vector<KeyPoint>& keypoints_;
std::vector<KeyPoint>& keypoints_;
const Mat& image_;
const Mat& mask_;
const Ptr<FeatureDetector>& detector_;
@@ -231,7 +229,7 @@ private:
public:
GridAdaptedFeatureDetectorInvoker(const Ptr<FeatureDetector>& detector, const Mat& image, const Mat& mask, vector<KeyPoint>& keypoints, int maxPerCell, int gridRows, int gridCols
GridAdaptedFeatureDetectorInvoker(const Ptr<FeatureDetector>& detector, const Mat& image, const Mat& mask, std::vector<KeyPoint>& keypoints, int maxPerCell, int gridRows, int gridCols
#ifdef HAVE_TBB
, tbb::mutex* kptLock
#endif
@@ -257,7 +255,7 @@ public:
Mat sub_mask;
if (!mask_.empty()) sub_mask = mask_(row_range, col_range);
vector<KeyPoint> sub_keypoints;
std::vector<KeyPoint> sub_keypoints;
sub_keypoints.reserve(maxPerCell_);
detector_->detect( sub_image, sub_keypoints, sub_mask );
@@ -279,7 +277,7 @@ public:
};
} // namepace
void GridAdaptedFeatureDetector::detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask ) const
void GridAdaptedFeatureDetector::detectImpl( const Mat& image, std::vector<KeyPoint>& keypoints, const Mat& mask ) const
{
if (image.empty() || maxTotalKeypoints < gridRows * gridCols)
{
@@ -310,7 +308,7 @@ bool PyramidAdaptedFeatureDetector::empty() const
return detector.empty() || (FeatureDetector*)detector->empty();
}
void PyramidAdaptedFeatureDetector::detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask ) const
void PyramidAdaptedFeatureDetector::detectImpl( const Mat& image, std::vector<KeyPoint>& keypoints, const Mat& mask ) const
{
Mat src = image;
Mat src_mask = mask;
@@ -327,9 +325,9 @@ void PyramidAdaptedFeatureDetector::detectImpl( const Mat& image, vector<KeyPoin
for( int l = 0, multiplier = 1; l <= maxLevel; ++l, multiplier *= 2 )
{
// Detect on current level of the pyramid
vector<KeyPoint> new_pts;
std::vector<KeyPoint> new_pts;
detector->detect( src, new_pts, src_mask );
vector<KeyPoint>::iterator it = new_pts.begin(),
std::vector<KeyPoint>::iterator it = new_pts.begin(),
end = new_pts.end();
for( ; it != end; ++it)
{