352 lines
16 KiB
C
352 lines
16 KiB
C
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//
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// This file is auto-generated. Please don't modify it!
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//
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#pragma once
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#ifdef __cplusplus
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//#import "opencv.hpp"
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#import "opencv2/features2d.hpp"
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#else
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#define CV_EXPORTS
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#endif
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#import <Foundation/Foundation.h>
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#import "Feature2D.h"
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NS_ASSUME_NONNULL_BEGIN
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// C++: class SIFT
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/**
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* Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform
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* (SIFT) algorithm by D. Lowe CITE: Lowe04 .
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*
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* Member of `Features2d`
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*/
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CV_EXPORTS @interface SIFT : Feature2D
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#ifdef __cplusplus
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@property(readonly)cv::Ptr<cv::SIFT> nativePtrSIFT;
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#endif
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#ifdef __cplusplus
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- (instancetype)initWithNativePtr:(cv::Ptr<cv::SIFT>)nativePtr;
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+ (instancetype)fromNative:(cv::Ptr<cv::SIFT>)nativePtr;
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#endif
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#pragma mark - Methods
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//
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// static Ptr_SIFT cv::SIFT::create(int nfeatures = 0, int nOctaveLayers = 3, double contrastThreshold = 0.04, double edgeThreshold = 10, double sigma = 1.6, bool enable_precise_upscale = false)
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//
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/**
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* @param nfeatures The number of best features to retain. The features are ranked by their scores
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* (measured in SIFT algorithm as the local contrast)
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*
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* @param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
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* number of octaves is computed automatically from the image resolution.
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*
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* @param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
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* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
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*
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* NOTE: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
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* nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
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* this argument to 0.09.
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*
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* @param edgeThreshold The threshold used to filter out edge-like features. Note that the its meaning
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* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
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* filtered out (more features are retained).
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*
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* @param sigma The sigma of the Gaussian applied to the input image at the octave \#0. If your image
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* is captured with a weak camera with soft lenses, you might want to reduce the number.
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*
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* @param enable_precise_upscale Whether to enable precise upscaling in the scale pyramid, which maps
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* index `$$\texttt{x}$$` to `$$\texttt{2x}$$`. This prevents localization bias. The option
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* is disabled by default.
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*/
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+ (SIFT*)create:(int)nfeatures nOctaveLayers:(int)nOctaveLayers contrastThreshold:(double)contrastThreshold edgeThreshold:(double)edgeThreshold sigma:(double)sigma enable_precise_upscale:(BOOL)enable_precise_upscale NS_SWIFT_NAME(create(nfeatures:nOctaveLayers:contrastThreshold:edgeThreshold:sigma:enable_precise_upscale:));
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/**
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* @param nfeatures The number of best features to retain. The features are ranked by their scores
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* (measured in SIFT algorithm as the local contrast)
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*
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* @param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
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* number of octaves is computed automatically from the image resolution.
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*
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* @param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
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* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
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*
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* NOTE: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
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* nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
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* this argument to 0.09.
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*
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* @param edgeThreshold The threshold used to filter out edge-like features. Note that the its meaning
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* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
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* filtered out (more features are retained).
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*
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* @param sigma The sigma of the Gaussian applied to the input image at the octave \#0. If your image
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* is captured with a weak camera with soft lenses, you might want to reduce the number.
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*
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* index `$$\texttt{x}$$` to `$$\texttt{2x}$$`. This prevents localization bias. The option
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* is disabled by default.
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*/
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+ (SIFT*)create:(int)nfeatures nOctaveLayers:(int)nOctaveLayers contrastThreshold:(double)contrastThreshold edgeThreshold:(double)edgeThreshold sigma:(double)sigma NS_SWIFT_NAME(create(nfeatures:nOctaveLayers:contrastThreshold:edgeThreshold:sigma:));
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/**
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* @param nfeatures The number of best features to retain. The features are ranked by their scores
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* (measured in SIFT algorithm as the local contrast)
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*
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* @param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
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* number of octaves is computed automatically from the image resolution.
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*
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* @param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
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* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
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*
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* NOTE: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
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* nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
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* this argument to 0.09.
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*
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* @param edgeThreshold The threshold used to filter out edge-like features. Note that the its meaning
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* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
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* filtered out (more features are retained).
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*
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* is captured with a weak camera with soft lenses, you might want to reduce the number.
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*
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* index `$$\texttt{x}$$` to `$$\texttt{2x}$$`. This prevents localization bias. The option
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* is disabled by default.
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*/
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+ (SIFT*)create:(int)nfeatures nOctaveLayers:(int)nOctaveLayers contrastThreshold:(double)contrastThreshold edgeThreshold:(double)edgeThreshold NS_SWIFT_NAME(create(nfeatures:nOctaveLayers:contrastThreshold:edgeThreshold:));
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/**
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* @param nfeatures The number of best features to retain. The features are ranked by their scores
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* (measured in SIFT algorithm as the local contrast)
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*
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* @param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
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* number of octaves is computed automatically from the image resolution.
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*
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* @param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
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* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
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*
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* NOTE: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
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* nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
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* this argument to 0.09.
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*
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* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
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* filtered out (more features are retained).
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*
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* is captured with a weak camera with soft lenses, you might want to reduce the number.
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*
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* index `$$\texttt{x}$$` to `$$\texttt{2x}$$`. This prevents localization bias. The option
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* is disabled by default.
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*/
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+ (SIFT*)create:(int)nfeatures nOctaveLayers:(int)nOctaveLayers contrastThreshold:(double)contrastThreshold NS_SWIFT_NAME(create(nfeatures:nOctaveLayers:contrastThreshold:));
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/**
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* @param nfeatures The number of best features to retain. The features are ranked by their scores
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* (measured in SIFT algorithm as the local contrast)
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*
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* @param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
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* number of octaves is computed automatically from the image resolution.
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*
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* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
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*
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* NOTE: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
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* nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
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* this argument to 0.09.
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*
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* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
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* filtered out (more features are retained).
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*
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* is captured with a weak camera with soft lenses, you might want to reduce the number.
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*
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* index `$$\texttt{x}$$` to `$$\texttt{2x}$$`. This prevents localization bias. The option
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* is disabled by default.
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*/
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+ (SIFT*)create:(int)nfeatures nOctaveLayers:(int)nOctaveLayers NS_SWIFT_NAME(create(nfeatures:nOctaveLayers:));
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/**
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* @param nfeatures The number of best features to retain. The features are ranked by their scores
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* (measured in SIFT algorithm as the local contrast)
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*
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* number of octaves is computed automatically from the image resolution.
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*
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* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
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*
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* NOTE: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
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* nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
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* this argument to 0.09.
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*
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* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
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* filtered out (more features are retained).
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*
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* is captured with a weak camera with soft lenses, you might want to reduce the number.
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*
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* index `$$\texttt{x}$$` to `$$\texttt{2x}$$`. This prevents localization bias. The option
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* is disabled by default.
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*/
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+ (SIFT*)create:(int)nfeatures NS_SWIFT_NAME(create(nfeatures:));
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/**
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* (measured in SIFT algorithm as the local contrast)
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*
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* number of octaves is computed automatically from the image resolution.
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*
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* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
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*
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* NOTE: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
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* nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
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* this argument to 0.09.
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*
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* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
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* filtered out (more features are retained).
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*
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* is captured with a weak camera with soft lenses, you might want to reduce the number.
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*
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* index `$$\texttt{x}$$` to `$$\texttt{2x}$$`. This prevents localization bias. The option
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* is disabled by default.
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*/
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+ (SIFT*)create NS_SWIFT_NAME(create());
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//
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// static Ptr_SIFT cv::SIFT::create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType, bool enable_precise_upscale = false)
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//
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/**
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* Create SIFT with specified descriptorType.
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* @param nfeatures The number of best features to retain. The features are ranked by their scores
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* (measured in SIFT algorithm as the local contrast)
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*
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* @param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
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* number of octaves is computed automatically from the image resolution.
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*
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* @param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
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* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
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*
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* NOTE: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
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* nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
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* this argument to 0.09.
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*
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* @param edgeThreshold The threshold used to filter out edge-like features. Note that the its meaning
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* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
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* filtered out (more features are retained).
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*
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* @param sigma The sigma of the Gaussian applied to the input image at the octave \#0. If your image
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* is captured with a weak camera with soft lenses, you might want to reduce the number.
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*
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* @param descriptorType The type of descriptors. Only CV_32F and CV_8U are supported.
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*
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* @param enable_precise_upscale Whether to enable precise upscaling in the scale pyramid, which maps
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* index `$$\texttt{x}$$` to `$$\texttt{2x}$$`. This prevents localization bias. The option
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* is disabled by default.
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*/
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+ (SIFT*)create:(int)nfeatures nOctaveLayers:(int)nOctaveLayers contrastThreshold:(double)contrastThreshold edgeThreshold:(double)edgeThreshold sigma:(double)sigma descriptorType:(int)descriptorType enable_precise_upscale:(BOOL)enable_precise_upscale NS_SWIFT_NAME(create(nfeatures:nOctaveLayers:contrastThreshold:edgeThreshold:sigma:descriptorType:enable_precise_upscale:));
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/**
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* Create SIFT with specified descriptorType.
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* @param nfeatures The number of best features to retain. The features are ranked by their scores
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* (measured in SIFT algorithm as the local contrast)
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*
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* @param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
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* number of octaves is computed automatically from the image resolution.
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*
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* @param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
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* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
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*
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* NOTE: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
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* nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
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* this argument to 0.09.
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*
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* @param edgeThreshold The threshold used to filter out edge-like features. Note that the its meaning
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* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
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* filtered out (more features are retained).
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*
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* @param sigma The sigma of the Gaussian applied to the input image at the octave \#0. If your image
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* is captured with a weak camera with soft lenses, you might want to reduce the number.
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*
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* @param descriptorType The type of descriptors. Only CV_32F and CV_8U are supported.
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*
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* index `$$\texttt{x}$$` to `$$\texttt{2x}$$`. This prevents localization bias. The option
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* is disabled by default.
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*/
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+ (SIFT*)create:(int)nfeatures nOctaveLayers:(int)nOctaveLayers contrastThreshold:(double)contrastThreshold edgeThreshold:(double)edgeThreshold sigma:(double)sigma descriptorType:(int)descriptorType NS_SWIFT_NAME(create(nfeatures:nOctaveLayers:contrastThreshold:edgeThreshold:sigma:descriptorType:));
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//
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// String cv::SIFT::getDefaultName()
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//
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- (NSString*)getDefaultName NS_SWIFT_NAME(getDefaultName());
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//
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// void cv::SIFT::setNFeatures(int maxFeatures)
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//
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- (void)setNFeatures:(int)maxFeatures NS_SWIFT_NAME(setNFeatures(maxFeatures:));
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//
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// int cv::SIFT::getNFeatures()
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//
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- (int)getNFeatures NS_SWIFT_NAME(getNFeatures());
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//
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// void cv::SIFT::setNOctaveLayers(int nOctaveLayers)
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//
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- (void)setNOctaveLayers:(int)nOctaveLayers NS_SWIFT_NAME(setNOctaveLayers(nOctaveLayers:));
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//
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// int cv::SIFT::getNOctaveLayers()
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//
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- (int)getNOctaveLayers NS_SWIFT_NAME(getNOctaveLayers());
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//
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// void cv::SIFT::setContrastThreshold(double contrastThreshold)
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//
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- (void)setContrastThreshold:(double)contrastThreshold NS_SWIFT_NAME(setContrastThreshold(contrastThreshold:));
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//
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// double cv::SIFT::getContrastThreshold()
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//
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- (double)getContrastThreshold NS_SWIFT_NAME(getContrastThreshold());
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//
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// void cv::SIFT::setEdgeThreshold(double edgeThreshold)
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//
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- (void)setEdgeThreshold:(double)edgeThreshold NS_SWIFT_NAME(setEdgeThreshold(edgeThreshold:));
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||
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//
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||
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// double cv::SIFT::getEdgeThreshold()
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||
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//
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||
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- (double)getEdgeThreshold NS_SWIFT_NAME(getEdgeThreshold());
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||
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||
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||
|
|
//
|
||
|
|
// void cv::SIFT::setSigma(double sigma)
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||
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|
//
|
||
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|
- (void)setSigma:(double)sigma NS_SWIFT_NAME(setSigma(sigma:));
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||
|
|
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||
|
|
|
||
|
|
//
|
||
|
|
// double cv::SIFT::getSigma()
|
||
|
|
//
|
||
|
|
- (double)getSigma NS_SWIFT_NAME(getSigma());
|
||
|
|
|
||
|
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|
||
|
|
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||
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|
@end
|
||
|
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||
|
|
NS_ASSUME_NONNULL_END
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||
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