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Added python macros

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pull/38/head
biagio montesano 10 years ago
parent 03acaf2c90
commit 29d7e471ef
2 changed files with 50 additions and 50 deletions
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  1. 96
      modules/line_descriptor/include/opencv2/line_descriptor/descriptor.hpp
  2. 4
      modules/line_descriptor/include/opencv2/line_descriptor/ed_line_detector.hpp

96
modules/line_descriptor/include/opencv2/line_descriptor/descriptor.hpp
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@ -60,45 +60,45 @@ class CV_EXPORTS_W KeyLine
{
public:
/* orientation of the line */
float angle;
CV_PROP_RW float angle;
/* object ID, that can be used to cluster keylines by the line they represent */
int class_id;
CV_PROP_RW int class_id;
/* octave (pyramid layer), from which the keyline has been extracted */
int octave;
CV_PROP_RW int octave;
/* coordinates of the middlepoint */
Point pt;
CV_PROP_RW Point pt;
/* the response, by which the strongest keylines have been selected.
It's represented by the ratio between line's length and maximum between
image's width and height */
float response;
CV_PROP_RW float response;
/* minimum area containing line */
float size;
CV_PROP_RW float size;
/* lines's extremes in original image */
float startPointX;
float startPointY;
float endPointX;
float endPointY;
CV_PROP_RW float startPointX;
CV_PROP_RW float startPointY;
CV_PROP_RW float endPointX;
CV_PROP_RW float endPointY;
/* line's extremes in image it was extracted from */
float sPointInOctaveX;
float sPointInOctaveY;
float ePointInOctaveX;
float ePointInOctaveY;
CV_PROP_RW float sPointInOctaveX;
CV_PROP_RW float sPointInOctaveY;
CV_PROP_RW float ePointInOctaveX;
CV_PROP_RW float ePointInOctaveY;
/* the length of line */
float lineLength;
CV_PROP_RW float lineLength;
/* number of pixels covered by the line */
unsigned int numOfPixels;
CV_PROP_RW unsigned int numOfPixels;
/* constructor */
KeyLine()
CV_WRAP KeyLine()
{
}
};
@ -128,10 +128,10 @@ class CV_EXPORTS_W BinaryDescriptor : public Algorithm
int ksize_;
/* read parameters from a FileNode object and store them (struct function) */
void read( const FileNode& fn );
CV_WRAP void read( const FileNode& fn );
/* store parameters to a FileStorage object (struct function) */
void write( FileStorage& fs ) const;
CV_WRAP void write( FileStorage& fs ) const;
};
@ -140,32 +140,32 @@ class CV_EXPORTS_W BinaryDescriptor : public Algorithm
BinaryDescriptor( const BinaryDescriptor::Params &parameters = BinaryDescriptor::Params() );
/* constructors with smart pointers */
static Ptr<BinaryDescriptor> createBinaryDescriptor();
static Ptr<BinaryDescriptor> createBinaryDescriptor( Params parameters );
CV_WRAP static Ptr<BinaryDescriptor> createBinaryDescriptor();
CV_WRAP static Ptr<BinaryDescriptor> createBinaryDescriptor( Params parameters );
/* destructor */
~BinaryDescriptor();
/* setters and getters */
int getNumOfOctaves();
void setNumOfOctaves( int octaves );
int getWidthOfBand();
void setWidthOfBand( int width );
int getReductionRatio();
void setReductionRatio( int rRatio );
CV_WRAP int getNumOfOctaves();
CV_WRAP void setNumOfOctaves( int octaves );
CV_WRAP int getWidthOfBand();
CV_WRAP void setWidthOfBand( int width );
CV_WRAP int getReductionRatio();
CV_WRAP void setReductionRatio( int rRatio );
/* reads parameters from a FileNode object and store them (class function ) */
virtual void read( const cv::FileNode& fn );
CV_WRAP virtual void read( const cv::FileNode& fn );
/* stores parameters to a FileStorage object (class function) */
virtual void write( cv::FileStorage& fs ) const;
CV_WRAP virtual void write( cv::FileStorage& fs ) const;
/* requires line detection (only one image) */
CV_WRAP
void detect( const Mat& image, CV_OUT std::vector<KeyLine>& keypoints, const Mat& mask = Mat() );
/* requires line detection (more than one image) */
void detect( const std::vector<Mat>& images, std::vector<std::vector<KeyLine> >& keylines, const std::vector<Mat>& masks =
CV_WRAP void detect( const std::vector<Mat>& images, std::vector<std::vector<KeyLine> >& keylines, const std::vector<Mat>& masks =
std::vector<Mat>() ) const;
/* requires descriptors computation (only one image) */
@ -173,17 +173,17 @@ class CV_EXPORTS_W BinaryDescriptor : public Algorithm
void compute( const Mat& image, CV_OUT CV_IN_OUT std::vector<KeyLine>& keylines, CV_OUT Mat& descriptors, bool returnFloatDescr = false ) const;
/* requires descriptors computation (more than one image) */
void compute( const std::vector<Mat>& images, std::vector<std::vector<KeyLine> >& keylines, std::vector<Mat>& descriptors, bool returnFloatDescr =
CV_WRAP void compute( const std::vector<Mat>& images, std::vector<std::vector<KeyLine> >& keylines, std::vector<Mat>& descriptors, bool returnFloatDescr =
false ) const;
/* returns descriptor size */
int descriptorSize() const;
CV_WRAP int descriptorSize() const;
/* returns data type */
int descriptorType() const;
CV_WRAP int descriptorType() const;
/* returns norm mode */
int defaultNorm() const;
CV_WRAP int defaultNorm() const;
/* definition of operator () */
CV_WRAP_AS(detectAndCompute)
@ -236,20 +236,20 @@ class CV_EXPORTS_W LSDDetector : public Algorithm
public:
/* constructor */
LSDDetector()
CV_WRAP LSDDetector()
{
}
;
/* constructor with smart pointer */
static Ptr<LSDDetector> createLSDDetector();
CV_WRAP static Ptr<LSDDetector> createLSDDetector();
/* requires line detection (only one image) */
CV_WRAP
void detect( const Mat& image, CV_OUT std::vector<KeyLine>& keypoints, int scale, int numOctaves, const Mat& mask = Mat() );
/* requires line detection (more than one image) */
void detect( const std::vector<Mat>& images, std::vector<std::vector<KeyLine> >& keylines, int scale, int numOctaves,
CV_WRAP void detect( const std::vector<Mat>& images, std::vector<std::vector<KeyLine> >& keylines, int scale, int numOctaves,
const std::vector<Mat>& masks = std::vector<Mat>() ) const;
private:
@ -273,47 +273,47 @@ class CV_EXPORTS_W BinaryDescriptorMatcher : public Algorithm
public:
/* for every input descriptor,
find the best matching one (for a pair of images) */
void match( const Mat& queryDescriptors, const Mat& trainDescriptors, std::vector<DMatch>& matches, const Mat& mask = Mat() ) const;
CV_WRAP void match( const Mat& queryDescriptors, const Mat& trainDescriptors, std::vector<DMatch>& matches, const Mat& mask = Mat() ) const;
/* for every input descriptor,
find the best matching one (from one image to a set) */
void match( const Mat& queryDescriptors, std::vector<DMatch>& matches, const std::vector<Mat>& masks = std::vector<Mat>() );
CV_WRAP void match( const Mat& queryDescriptors, std::vector<DMatch>& matches, const std::vector<Mat>& masks = std::vector<Mat>() );
/* for every input descriptor,
find the best k matching descriptors (for a pair of images) */
void knnMatch( const Mat& queryDescriptors, const Mat& trainDescriptors, std::vector<std::vector<DMatch> >& matches, int k, const Mat& mask = Mat(),
CV_WRAP void knnMatch( const Mat& queryDescriptors, const Mat& trainDescriptors, std::vector<std::vector<DMatch> >& matches, int k, const Mat& mask = Mat(),
bool compactResult = false ) const;
/* for every input descriptor,
find the best k matching descriptors (from one image to a set) */
void knnMatch( const Mat& queryDescriptors, std::vector<std::vector<DMatch> >& matches, int k, const std::vector<Mat>& masks = std::vector<Mat>(),
CV_WRAP void knnMatch( const Mat& queryDescriptors, std::vector<std::vector<DMatch> >& matches, int k, const std::vector<Mat>& masks = std::vector<Mat>(),
bool compactResult = false );
/* for every input descriptor, find all the ones falling in a
certain matching radius (for a pair of images) */
void radiusMatch( const Mat& queryDescriptors, const Mat& trainDescriptors, std::vector<std::vector<DMatch> >& matches, float maxDistance,
CV_WRAP void radiusMatch( const Mat& queryDescriptors, const Mat& trainDescriptors, std::vector<std::vector<DMatch> >& matches, float maxDistance,
const Mat& mask = Mat(), bool compactResult = false ) const;
/* for every input descriptor, find all the ones falling in a
certain matching radius (from one image to a set) */
void radiusMatch( const Mat& queryDescriptors, std::vector<std::vector<DMatch> >& matches, float maxDistance, const std::vector<Mat>& masks =
CV_WRAP void radiusMatch( const Mat& queryDescriptors, std::vector<std::vector<DMatch> >& matches, float maxDistance, const std::vector<Mat>& masks =
std::vector<Mat>(),
bool compactResult = false );
/* store new descriptors to be inserted in dataset */
void add( const std::vector<Mat>& descriptors );
CV_WRAP void add( const std::vector<Mat>& descriptors );
/* store new descriptors into dataset */
void train();
CV_WRAP void train();
/* constructor with smart pointer */
static Ptr<BinaryDescriptorMatcher> createBinaryDescriptorMatcher();
CV_WRAP static Ptr<BinaryDescriptorMatcher> createBinaryDescriptorMatcher();
/* clear dataset and internal data */
void clear();
CV_WRAP void clear();
/* constructor */
BinaryDescriptorMatcher();
CV_WRAP BinaryDescriptorMatcher();
/* destructor */
~BinaryDescriptorMatcher()

4
modules/line_descriptor/include/opencv2/line_descriptor/ed_line_detector.hpp
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@ -85,7 +85,7 @@ struct EDLineParam
};
#define RELATIVE_ERROR_FACTOR 100.0
#define M_LN10 2.30258509299404568402
#define MLN10 2.30258509299404568402
#define log_gamma(x) ((x)>15.0?log_gamma_windschitl(x):log_gamma_lanczos(x))
/* This class is used to detect lines from input image.
@ -425,7 +425,7 @@ class EDLineDetector
if( double_equal( term, 0.0 ) )
{ /* the first term is almost zero */
if( (double) k > (double) n * p ) /* at begin or end of the tail? */
return -log1term / M_LN10 - logNT; /* end: use just the first term */
return -log1term / MLN10 - logNT; /* end: use just the first term */
else
return -logNT; /* begin: the tail is roughly 1 */
}

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