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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106
modules/objdetect/include/opencv2/objdetect/objdetect.hpp
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@@ -307,32 +307,32 @@ public:
};
LatentSvmDetector();
LatentSvmDetector( const vector<string>& filenames, const vector<string>& classNames=vector<string>() );
LatentSvmDetector( const std::vector<std::string>& filenames, const std::vector<std::string>& classNames=std::vector<std::string>() );
virtual ~LatentSvmDetector();
virtual void clear();
virtual bool empty() const;
bool load( const vector<string>& filenames, const vector<string>& classNames=vector<string>() );
bool load( const std::vector<std::string>& filenames, const std::vector<std::string>& classNames=std::vector<std::string>() );
virtual void detect( const Mat& image,
vector<ObjectDetection>& objectDetections,
std::vector<ObjectDetection>& objectDetections,
float overlapThreshold=0.5f,
int numThreads=-1 );
const vector<string>& getClassNames() const;
const std::vector<std::string>& getClassNames() const;
size_t getClassCount() const;
private:
vector<CvLatentSvmDetector*> detectors;
vector<string> classNames;
std::vector<CvLatentSvmDetector*> detectors;
std::vector<std::string> classNames;
};
CV_EXPORTS void groupRectangles(CV_OUT CV_IN_OUT vector<Rect>& rectList, int groupThreshold, double eps=0.2);
CV_EXPORTS_W void groupRectangles(CV_OUT CV_IN_OUT vector<Rect>& rectList, CV_OUT vector<int>& weights, int groupThreshold, double eps=0.2);
CV_EXPORTS void groupRectangles( vector<Rect>& rectList, int groupThreshold, double eps, vector<int>* weights, vector<double>* levelWeights );
CV_EXPORTS void groupRectangles(vector<Rect>& rectList, vector<int>& rejectLevels,
vector<double>& levelWeights, int groupThreshold, double eps=0.2);
CV_EXPORTS void groupRectangles_meanshift(vector<Rect>& rectList, vector<double>& foundWeights, vector<double>& foundScales,
CV_EXPORTS void groupRectangles(CV_OUT CV_IN_OUT std::vector<Rect>& rectList, int groupThreshold, double eps=0.2);
CV_EXPORTS_W void groupRectangles(CV_OUT CV_IN_OUT std::vector<Rect>& rectList, CV_OUT std::vector<int>& weights, int groupThreshold, double eps=0.2);
CV_EXPORTS void groupRectangles( std::vector<Rect>& rectList, int groupThreshold, double eps, std::vector<int>* weights, std::vector<double>* levelWeights );
CV_EXPORTS void groupRectangles(std::vector<Rect>& rectList, std::vector<int>& rejectLevels,
std::vector<double>& levelWeights, int groupThreshold, double eps=0.2);
CV_EXPORTS void groupRectangles_meanshift(std::vector<Rect>& rectList, std::vector<double>& foundWeights, std::vector<double>& foundScales,
double detectThreshold = 0.0, Size winDetSize = Size(64, 128));
@@ -369,23 +369,23 @@ class CV_EXPORTS_W CascadeClassifier
{
public:
CV_WRAP CascadeClassifier();
CV_WRAP CascadeClassifier( const string& filename );
CV_WRAP CascadeClassifier( const std::string& filename );
virtual ~CascadeClassifier();
CV_WRAP virtual bool empty() const;
CV_WRAP bool load( const string& filename );
CV_WRAP bool load( const std::string& filename );
virtual bool read( const FileNode& node );
CV_WRAP virtual void detectMultiScale( const Mat& image,
CV_OUT vector<Rect>& objects,
CV_OUT std::vector<Rect>& objects,
double scaleFactor=1.1,
int minNeighbors=3, int flags=0,
Size minSize=Size(),
Size maxSize=Size() );
CV_WRAP virtual void detectMultiScale( const Mat& image,
CV_OUT vector<Rect>& objects,
vector<int>& rejectLevels,
vector<double>& levelWeights,
CV_OUT std::vector<Rect>& objects,
std::vector<int>& rejectLevels,
std::vector<double>& levelWeights,
double scaleFactor=1.1,
int minNeighbors=3, int flags=0,
Size minSize=Size(),
@@ -400,11 +400,11 @@ public:
protected:
//virtual bool detectSingleScale( const Mat& image, int stripCount, Size processingRectSize,
// int stripSize, int yStep, double factor, vector<Rect>& candidates );
// int stripSize, int yStep, double factor, std::vector<Rect>& candidates );
virtual bool detectSingleScale( const Mat& image, int stripCount, Size processingRectSize,
int stripSize, int yStep, double factor, vector<Rect>& candidates,
vector<int>& rejectLevels, vector<double>& levelWeights, bool outputRejectLevels=false);
int stripSize, int yStep, double factor, std::vector<Rect>& candidates,
std::vector<int>& rejectLevels, std::vector<double>& levelWeights, bool outputRejectLevels=false);
protected:
enum { BOOST = 0 };
@@ -460,11 +460,11 @@ protected:
int ncategories;
Size origWinSize;
vector<Stage> stages;
vector<DTree> classifiers;
vector<DTreeNode> nodes;
vector<float> leaves;
vector<int> subsets;
std::vector<Stage> stages;
std::vector<DTree> classifiers;
std::vector<DTreeNode> nodes;
std::vector<float> leaves;
std::vector<int> subsets;
};
Data data;
@@ -496,9 +496,9 @@ struct DetectionROI
// scale(size) of the bounding box
double scale;
// set of requrested locations to be evaluated
vector<cv::Point> locations;
std::vector<cv::Point> locations;
// vector that will contain confidence values for each location
vector<double> confidences;
std::vector<double> confidences;
};
struct CV_EXPORTS_W HOGDescriptor
@@ -524,7 +524,7 @@ public:
gammaCorrection(_gammaCorrection), nlevels(_nlevels)
{}
CV_WRAP HOGDescriptor(const String& filename)
CV_WRAP HOGDescriptor(const std::string& filename)
{
load(filename);
}
@@ -543,34 +543,34 @@ public:
CV_WRAP virtual void setSVMDetector(InputArray _svmdetector);
virtual bool read(FileNode& fn);
virtual void write(FileStorage& fs, const String& objname) const;
virtual void write(FileStorage& fs, const std::string& objname) const;
CV_WRAP virtual bool load(const String& filename, const String& objname=String());
CV_WRAP virtual void save(const String& filename, const String& objname=String()) const;
CV_WRAP virtual bool load(const std::string& filename, const std::string& objname=std::string());
CV_WRAP virtual void save(const std::string& filename, const std::string& objname=std::string()) const;
virtual void copyTo(HOGDescriptor& c) const;
CV_WRAP virtual void compute(const Mat& img,
CV_OUT vector<float>& descriptors,
CV_OUT std::vector<float>& descriptors,
Size winStride=Size(), Size padding=Size(),
const vector<Point>& locations=vector<Point>()) const;
const std::vector<Point>& locations=std::vector<Point>()) const;
//with found weights output
CV_WRAP virtual void detect(const Mat& img, CV_OUT vector<Point>& foundLocations,
CV_OUT vector<double>& weights,
CV_WRAP virtual void detect(const Mat& img, CV_OUT std::vector<Point>& foundLocations,
CV_OUT std::vector<double>& weights,
double hitThreshold=0, Size winStride=Size(),
Size padding=Size(),
const vector<Point>& searchLocations=vector<Point>()) const;
const std::vector<Point>& searchLocations=std::vector<Point>()) const;
//without found weights output
virtual void detect(const Mat& img, CV_OUT vector<Point>& foundLocations,
virtual void detect(const Mat& img, CV_OUT std::vector<Point>& foundLocations,
double hitThreshold=0, Size winStride=Size(),
Size padding=Size(),
const vector<Point>& searchLocations=vector<Point>()) const;
const std::vector<Point>& searchLocations=std::vector<Point>()) const;
//with result weights output
CV_WRAP virtual void detectMultiScale(const Mat& img, CV_OUT vector<Rect>& foundLocations,
CV_OUT vector<double>& foundWeights, double hitThreshold=0,
CV_WRAP virtual void detectMultiScale(const Mat& img, CV_OUT std::vector<Rect>& foundLocations,
CV_OUT std::vector<double>& foundWeights, double hitThreshold=0,
Size winStride=Size(), Size padding=Size(), double scale=1.05,
double finalThreshold=2.0,bool useMeanshiftGrouping = false) const;
//without found weights output
virtual void detectMultiScale(const Mat& img, CV_OUT vector<Rect>& foundLocations,
virtual void detectMultiScale(const Mat& img, CV_OUT std::vector<Rect>& foundLocations,
double hitThreshold=0, Size winStride=Size(),
Size padding=Size(), double scale=1.05,
double finalThreshold=2.0, bool useMeanshiftGrouping = false) const;
@@ -578,8 +578,8 @@ public:
CV_WRAP virtual void computeGradient(const Mat& img, CV_OUT Mat& grad, CV_OUT Mat& angleOfs,
Size paddingTL=Size(), Size paddingBR=Size()) const;
CV_WRAP static vector<float> getDefaultPeopleDetector();
CV_WRAP static vector<float> getDaimlerPeopleDetector();
CV_WRAP static std::vector<float> getDefaultPeopleDetector();
CV_WRAP static std::vector<float> getDaimlerPeopleDetector();
CV_PROP Size winSize;
CV_PROP Size blockSize;
@@ -591,12 +591,12 @@ public:
CV_PROP int histogramNormType;
CV_PROP double L2HysThreshold;
CV_PROP bool gammaCorrection;
CV_PROP vector<float> svmDetector;
CV_PROP std::vector<float> svmDetector;
CV_PROP int nlevels;
// evaluate specified ROI and return confidence value for each location
virtual void detectROI(const cv::Mat& img, const vector<cv::Point> &locations,
virtual void 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 = 0, cv::Size winStride = Size(),
cv::Size padding = Size()) const;
@@ -614,11 +614,11 @@ public:
CV_EXPORTS_W void findDataMatrix(InputArray image,
CV_OUT vector<string>& codes,
CV_OUT std::vector<std::string>& codes,
OutputArray corners=noArray(),
OutputArrayOfArrays dmtx=noArray());
CV_EXPORTS_W void drawDataMatrixCodes(InputOutputArray image,
const vector<string>& codes,
const std::vector<std::string>& codes,
InputArray corners);
}
@@ -641,16 +641,6 @@ CV_EXPORTS std::deque<CvDataMatrixCode> cvFindDataMatrix(CvMat *im);
namespace cv {
namespace linemod {
using cv::FileNode;
using cv::FileStorage;
using cv::Mat;
using cv::noArray;
using cv::OutputArrayOfArrays;
using cv::Point;
using cv::Ptr;
using cv::Rect;
using cv::Size;
/// @todo Convert doxy comments to rst
/**