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ORBExtractor.h
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97 lines (66 loc) · 2.09 KB
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#pragma once
#include <vector>
#include <list>
namespace TORB {
class ExtractorNode
{
public:
ExtractorNode() :bNoMore(false) {}
void DivideNode(ExtractorNode& n1, ExtractorNode& n2, ExtractorNode& n3, ExtractorNode& n4);
std::vector<cv::KeyPoint> vKeys;
cv::Point2i UL, UR, BL, BR;
std::list<ExtractorNode>::iterator lit;
bool bNoMore;
};
class ORBExtractor
{
public:
enum { HARRIS_SCORE = 0, FAST_SCORE = 1 };
ORBExtractor(int nfeatures, float scaleFactor, int nlevels,
int iniThFAST, int minThFAST);
~ORBExtractor() {}
// Compute the ORB features and descriptors on an image.
// ORB are dispersed on the image using an octree.
// Mask is ignored in the current implementation.
void operator()(cv::InputArray image, cv::InputArray mask,
std::vector<cv::KeyPoint>& keypoints,
cv::OutputArray descriptors);
int inline GetLevels() {
return nlevels;
}
float inline GetScaleFactor() {
return scaleFactor;
}
std::vector<float> inline GetScaleFactors() {
return mvScaleFactor;
}
std::vector<float> inline GetInverseScaleFactors() {
return mvInvScaleFactor;
}
std::vector<float> inline GetScaleSigmaSquares() {
return mvLevelSigma2;
}
std::vector<float> inline GetInverseScaleSigmaSquares() {
return mvInvLevelSigma2;
}
std::vector<cv::Mat> mvImagePyramid;
protected:
void ComputePyramid(cv::Mat image);
void ComputeKeyPointsOctTree(std::vector<std::vector<cv::KeyPoint> >& allKeypoints);
std::vector<cv::KeyPoint> DistributeOctTree(const std::vector<cv::KeyPoint>& vToDistributeKeys, const int& minX,
const int& maxX, const int& minY, const int& maxY, const int& nFeatures, const int& level);
//void ComputeKeyPointsOld(std::vector<std::vector<cv::KeyPoint> >& allKeypoints);
std::vector<cv::Point> pattern;
int nfeatures;
double scaleFactor;
int nlevels;
int iniThFAST;
int minThFAST;
std::vector<int> mnFeaturesPerLevel;
std::vector<int> umax;
std::vector<float> mvScaleFactor;
std::vector<float> mvInvScaleFactor;
std::vector<float> mvLevelSigma2;
std::vector<float> mvInvLevelSigma2;
};
}