generic-library/opencv
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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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54
modules/objdetect/src/hog.cpp
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@@ -120,7 +120,7 @@ bool HOGDescriptor::read(FileNode& obj)
return true;
}
void HOGDescriptor::write(FileStorage& fs, const String& objName) const
void HOGDescriptor::write(FileStorage& fs, const std::string& objName) const
{
if( !objName.empty() )
fs << objName;
@@ -142,14 +142,14 @@ void HOGDescriptor::write(FileStorage& fs, const String& objName) const
fs << "}";
}
bool HOGDescriptor::load(const String& filename, const String& objname)
bool HOGDescriptor::load(const std::string& filename, const std::string& objname)
{
FileStorage fs(filename, FileStorage::READ);
FileNode obj = !objname.empty() ? fs[objname] : fs.getFirstTopLevelNode();
return read(obj);
}
void HOGDescriptor::save(const String& filename, const String& objName) const
void HOGDescriptor::save(const std::string& filename, const std::string& objName) const
{
FileStorage fs(filename, FileStorage::WRITE);
write(fs, !objName.empty() ? objName : FileStorage::getDefaultObjectName(filename));
@@ -409,11 +409,11 @@ struct HOGCache
const float* getBlock(Point pt, float* buf);
virtual void normalizeBlockHistogram(float* histogram) const;
vector<PixData> pixData;
vector<BlockData> blockData;
std::vector<PixData> pixData;
std::vector<BlockData> blockData;
bool useCache;
vector<int> ymaxCached;
std::vector<int> ymaxCached;
Size winSize, cacheStride;
Size nblocks, ncells;
int blockHistogramSize;
@@ -791,9 +791,9 @@ Rect HOGCache::getWindow(Size imageSize, Size winStride, int idx) const
}
void HOGDescriptor::compute(const Mat& img, vector<float>& descriptors,
void HOGDescriptor::compute(const Mat& img, std::vector<float>& descriptors,
Size winStride, Size padding,
const vector<Point>& locations) const
const std::vector<Point>& locations) const
{
if( winStride == Size() )
winStride = cellSize;
@@ -854,8 +854,8 @@ void HOGDescriptor::compute(const Mat& img, vector<float>& descriptors,
void HOGDescriptor::detect(const Mat& img,
vector<Point>& hits, vector<double>& weights, double hitThreshold,
Size winStride, Size padding, const vector<Point>& locations) const
std::vector<Point>& hits, std::vector<double>& weights, double hitThreshold,
Size winStride, Size padding, const std::vector<Point>& locations) const
{
hits.clear();
if( svmDetector.empty() )
@@ -882,7 +882,7 @@ void HOGDescriptor::detect(const Mat& img,
size_t dsize = getDescriptorSize();
double rho = svmDetector.size() > dsize ? svmDetector[dsize] : 0;
vector<float> blockHist(blockHistogramSize);
std::vector<float> blockHist(blockHistogramSize);
for( size_t i = 0; i < nwindows; i++ )
{
@@ -932,10 +932,10 @@ void HOGDescriptor::detect(const Mat& img,
}
}
void HOGDescriptor::detect(const Mat& img, vector<Point>& hits, double hitThreshold,
Size winStride, Size padding, const vector<Point>& locations) const
void HOGDescriptor::detect(const Mat& img, std::vector<Point>& hits, double hitThreshold,
Size winStride, Size padding, const std::vector<Point>& locations) const
{
vector<double> weightsV;
std::vector<double> weightsV;
detect(img, hits, weightsV, hitThreshold, winStride, padding, locations);
}
@@ -965,8 +965,8 @@ public:
double minScale = i1 > 0 ? levelScale[i1] : i2 > 1 ? levelScale[i1+1] : std::max(img.cols, img.rows);
Size maxSz(cvCeil(img.cols/minScale), cvCeil(img.rows/minScale));
Mat smallerImgBuf(maxSz, img.type());
vector<Point> locations;
vector<double> hitsWeights;
std::vector<Point> locations;
std::vector<double> hitsWeights;
for( i = i1; i < i2; i++ )
{
@@ -1019,14 +1019,14 @@ public:
void HOGDescriptor::detectMultiScale(
const Mat& img, vector<Rect>& foundLocations, vector<double>& foundWeights,
const Mat& img, std::vector<Rect>& foundLocations, std::vector<double>& foundWeights,
double hitThreshold, Size winStride, Size padding,
double scale0, double finalThreshold, bool useMeanshiftGrouping) const
{
double scale = 1.;
int levels = 0;
vector<double> levelScale;
std::vector<double> levelScale;
for( levels = 0; levels < nlevels; levels++ )
{
levelScale.push_back(scale);
@@ -1064,11 +1064,11 @@ void HOGDescriptor::detectMultiScale(
}
}
void HOGDescriptor::detectMultiScale(const Mat& img, vector<Rect>& foundLocations,
void HOGDescriptor::detectMultiScale(const Mat& img, std::vector<Rect>& foundLocations,
double hitThreshold, Size winStride, Size padding,
double scale0, double finalThreshold, bool useMeanshiftGrouping) const
{
vector<double> foundWeights;
std::vector<double> foundWeights;
detectMultiScale(img, foundLocations, foundWeights, hitThreshold, winStride,
padding, scale0, finalThreshold, useMeanshiftGrouping);
}
@@ -1078,7 +1078,7 @@ typedef RTTIImpl<HOGDescriptor> HOGRTTI;
CvType hog_type( CV_TYPE_NAME_HOG_DESCRIPTOR, HOGRTTI::isInstance,
HOGRTTI::release, HOGRTTI::read, HOGRTTI::write, HOGRTTI::clone);
vector<float> HOGDescriptor::getDefaultPeopleDetector()
std::vector<float> HOGDescriptor::getDefaultPeopleDetector()
{
static const float detector[] = {
0.05359386f, -0.14721455f, -0.05532170f, 0.05077307f,
@@ -1886,11 +1886,11 @@ vector<float> HOGDescriptor::getDefaultPeopleDetector()
-0.01612278f, -1.46097376e-003f, 0.14013411f, -8.96181818e-003f,
-0.03250246f, 3.38630192e-003f, 2.64779478e-003f, 0.03359732f,
-0.02411991f, -0.04229729f, 0.10666174f, -6.66579151f };
return vector<float>(detector, detector + sizeof(detector)/sizeof(detector[0]));
return std::vector<float>(detector, detector + sizeof(detector)/sizeof(detector[0]));
}
//This function renurn 1981 SVM coeffs obtained from daimler's base.
//To use these coeffs the detection window size should be (48,96)
vector<float> HOGDescriptor::getDaimlerPeopleDetector()
std::vector<float> HOGDescriptor::getDaimlerPeopleDetector()
{
static const float detector[] = {
0.294350f, -0.098796f, -0.129522f, 0.078753f,
@@ -2389,7 +2389,7 @@ vector<float> HOGDescriptor::getDaimlerPeopleDetector()
-0.025054f, -0.093026f, -0.035372f, -0.233209f,
-0.049869f, -0.039151f, -0.022279f, -0.065380f,
-9.063785f};
return vector<float>(detector, detector + sizeof(detector)/sizeof(detector[0]));
return std::vector<float>(detector, detector + sizeof(detector)/sizeof(detector[0]));
}
class HOGConfInvoker : public ParallelLoopBody
@@ -2415,7 +2415,7 @@ public:
Size maxSz(cvCeil(img.cols/(*locations)[0].scale), cvCeil(img.rows/(*locations)[0].scale));
Mat smallerImgBuf(maxSz, img.type());
vector<Point> dets;
std::vector<Point> dets;
for( i = i1; i < i2; i++ )
{
@@ -2451,7 +2451,7 @@ public:
Mutex* mtx;
};
void HOGDescriptor::detectROI(const cv::Mat& img, const vector<cv::Point> &locations,
void HOGDescriptor::detectROI(const cv::Mat& img, const std::vector<cv::Point> &locations,
CV_OUT std::vector<cv::Point>& foundLocations, CV_OUT std::vector<double>& confidences,
double hitThreshold, cv::Size winStride,
cv::Size padding) const
@@ -2489,7 +2489,7 @@ void HOGDescriptor::detectROI(const cv::Mat& img, const vector<cv::Point> &locat
size_t dsize = getDescriptorSize();
double rho = svmDetector.size() > dsize ? svmDetector[dsize] : 0;
vector<float> blockHist(blockHistogramSize);
std::vector<float> blockHist(blockHistogramSize);
for( size_t i = 0; i < nwindows; i++ )
{