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Merge pull request #2449 from saskatchewancatch:issue-16736

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* issue-16736: quick step towards moving SIFT from non-free to free. Moves
include, tests, and implementation to free area.
This commit is contained in:
RAJKIRAN NATARAJAN
2020-03-09 12:41:20 -07:00
committed by GitHub
parent 9c0ae273fd
commit f3982616a8
4 changed files with 38 additions and 49 deletions
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33
modules/xfeatures2d/include/opencv2/xfeatures2d.hpp
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@@ -65,6 +65,39 @@ namespace cv
namespace xfeatures2d
{
/** @brief Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform
(SIFT) algorithm by D. Lowe @cite Lowe04 .
*/
class CV_EXPORTS_W SIFT : public Feature2D
{
public:
/**
@param nfeatures The number of best features to retain. The features are ranked by their scores
(measured in SIFT algorithm as the local contrast)
@param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
number of octaves is computed automatically from the image resolution.
@param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
(low-contrast) regions. The larger the threshold, the less features are produced by the detector.
@param edgeThreshold The threshold used to filter out edge-like features. Note that the its meaning
is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
filtered out (more features are retained).
@param sigma The sigma of the Gaussian applied to the input image at the octave \#0. If your image
is captured with a weak camera with soft lenses, you might want to reduce the number.
*/
CV_WRAP static Ptr<SIFT> create(int nfeatures = 0, int nOctaveLayers = 3,
double contrastThreshold = 0.04, double edgeThreshold = 10,
double sigma = 1.6);
};
typedef SIFT SiftFeatureDetector;
typedef SIFT SiftDescriptorExtractor;
//! @addtogroup xfeatures2d_experiment
//! @{

34
modules/xfeatures2d/include/opencv2/xfeatures2d/nonfree.hpp
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@@ -50,40 +50,6 @@ namespace cv
namespace xfeatures2d
{
//! @addtogroup xfeatures2d_nonfree
//! @{
/** @brief Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform
(SIFT) algorithm by D. Lowe @cite Lowe04 .
*/
class CV_EXPORTS_W SIFT : public Feature2D
{
public:
/**
@param nfeatures The number of best features to retain. The features are ranked by their scores
(measured in SIFT algorithm as the local contrast)
@param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
number of octaves is computed automatically from the image resolution.
@param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
(low-contrast) regions. The larger the threshold, the less features are produced by the detector.
@param edgeThreshold The threshold used to filter out edge-like features. Note that the its meaning
is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
filtered out (more features are retained).
@param sigma The sigma of the Gaussian applied to the input image at the octave \#0. If your image
is captured with a weak camera with soft lenses, you might want to reduce the number.
*/
CV_WRAP static Ptr<SIFT> create( int nfeatures = 0, int nOctaveLayers = 3,
double contrastThreshold = 0.04, double edgeThreshold = 10,
double sigma = 1.6);
};
typedef SIFT SiftFeatureDetector;
typedef SIFT SiftDescriptorExtractor;
/** @brief Class for extracting Speeded Up Robust Features from an image @cite Bay06 .
The algorithm parameters: