590 lines
24 KiB
C#
590 lines
24 KiB
C#
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using OpenCVForUnity.CoreModule;
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using OpenCVForUnity.UtilsModule;
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using System;
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using System.Collections.Generic;
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using System.Runtime.InteropServices;
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namespace OpenCVForUnity.Features2dModule
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{
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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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public class SIFT : Feature2D
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{
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protected override void Dispose(bool disposing)
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{
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try
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{
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if (disposing)
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{
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}
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if (IsEnabledDispose)
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{
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if (nativeObj != IntPtr.Zero)
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features2d_SIFT_delete(nativeObj);
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nativeObj = IntPtr.Zero;
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}
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}
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finally
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{
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base.Dispose(disposing);
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}
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}
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protected internal SIFT(IntPtr addr) : base(addr) { }
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// internal usage only
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public static new SIFT __fromPtr__(IntPtr addr) { return new SIFT(addr); }
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//
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// C++: 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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* <b>Note:</b> 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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* return automatically generated
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*/
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public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, bool enable_precise_upscale)
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{
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return SIFT.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_SIFT_create_10(nfeatures, nOctaveLayers, contrastThreshold, edgeThreshold, sigma, enable_precise_upscale)));
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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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* <b>Note:</b> 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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* return automatically generated
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*/
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public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma)
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{
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return SIFT.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_SIFT_create_11(nfeatures, nOctaveLayers, contrastThreshold, edgeThreshold, sigma)));
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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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* <b>Note:</b> 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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* return automatically generated
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*/
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public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold)
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{
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return SIFT.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_SIFT_create_12(nfeatures, nOctaveLayers, contrastThreshold, edgeThreshold)));
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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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* <b>Note:</b> 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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* return automatically generated
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*/
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public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold)
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{
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return SIFT.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_SIFT_create_13(nfeatures, nOctaveLayers, contrastThreshold)));
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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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* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
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*
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* <b>Note:</b> 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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* return automatically generated
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*/
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public static SIFT create(int nfeatures, int nOctaveLayers)
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{
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return SIFT.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_SIFT_create_14(nfeatures, nOctaveLayers)));
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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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* 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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* <b>Note:</b> 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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* return automatically generated
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*/
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public static SIFT create(int nfeatures)
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{
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return SIFT.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_SIFT_create_15(nfeatures)));
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}
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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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* <b>Note:</b> 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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* return automatically generated
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*/
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public static SIFT create()
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{
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return SIFT.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_SIFT_create_16()));
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}
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//
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// C++: 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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* <b>Note:</b> 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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* return automatically generated
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*/
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public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType, bool enable_precise_upscale)
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{
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return SIFT.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_SIFT_create_17(nfeatures, nOctaveLayers, contrastThreshold, edgeThreshold, sigma, descriptorType, enable_precise_upscale)));
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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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* <b>Note:</b> 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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* return automatically generated
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*/
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public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType)
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{
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return SIFT.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_SIFT_create_18(nfeatures, nOctaveLayers, contrastThreshold, edgeThreshold, sigma, descriptorType)));
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}
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//
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// C++: String cv::SIFT::getDefaultName()
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//
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public override string getDefaultName()
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{
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ThrowIfDisposed();
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string retVal = Marshal.PtrToStringAnsi(DisposableObject.ThrowIfNullIntPtr(features2d_SIFT_getDefaultName_10(nativeObj)));
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return retVal;
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}
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//
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// C++: void cv::SIFT::setNFeatures(int maxFeatures)
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//
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public void setNFeatures(int maxFeatures)
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{
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ThrowIfDisposed();
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features2d_SIFT_setNFeatures_10(nativeObj, maxFeatures);
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}
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//
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// C++: int cv::SIFT::getNFeatures()
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//
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public int getNFeatures()
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{
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ThrowIfDisposed();
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return features2d_SIFT_getNFeatures_10(nativeObj);
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}
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//
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// C++: void cv::SIFT::setNOctaveLayers(int nOctaveLayers)
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//
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public void setNOctaveLayers(int nOctaveLayers)
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{
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ThrowIfDisposed();
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features2d_SIFT_setNOctaveLayers_10(nativeObj, nOctaveLayers);
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}
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//
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// C++: int cv::SIFT::getNOctaveLayers()
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//
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public int getNOctaveLayers()
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{
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ThrowIfDisposed();
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return features2d_SIFT_getNOctaveLayers_10(nativeObj);
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}
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//
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// C++: void cv::SIFT::setContrastThreshold(double contrastThreshold)
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//
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public void setContrastThreshold(double contrastThreshold)
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{
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ThrowIfDisposed();
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features2d_SIFT_setContrastThreshold_10(nativeObj, contrastThreshold);
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}
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//
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// C++: double cv::SIFT::getContrastThreshold()
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//
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public double getContrastThreshold()
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{
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ThrowIfDisposed();
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return features2d_SIFT_getContrastThreshold_10(nativeObj);
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}
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//
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// C++: void cv::SIFT::setEdgeThreshold(double edgeThreshold)
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//
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public void setEdgeThreshold(double edgeThreshold)
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{
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ThrowIfDisposed();
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features2d_SIFT_setEdgeThreshold_10(nativeObj, edgeThreshold);
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}
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//
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// C++: double cv::SIFT::getEdgeThreshold()
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//
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public double getEdgeThreshold()
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{
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ThrowIfDisposed();
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return features2d_SIFT_getEdgeThreshold_10(nativeObj);
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}
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//
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// C++: void cv::SIFT::setSigma(double sigma)
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//
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public void setSigma(double sigma)
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{
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ThrowIfDisposed();
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features2d_SIFT_setSigma_10(nativeObj, sigma);
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}
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//
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// C++: double cv::SIFT::getSigma()
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//
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public double getSigma()
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{
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ThrowIfDisposed();
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return features2d_SIFT_getSigma_10(nativeObj);
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}
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#if (UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR
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const string LIBNAME = "__Internal";
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#else
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const string LIBNAME = "opencvforunity";
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#endif
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// C++: 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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[DllImport(LIBNAME)]
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private static extern IntPtr features2d_SIFT_create_10(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, [MarshalAs(UnmanagedType.U1)] bool enable_precise_upscale);
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[DllImport(LIBNAME)]
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private static extern IntPtr features2d_SIFT_create_11(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma);
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[DllImport(LIBNAME)]
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private static extern IntPtr features2d_SIFT_create_12(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold);
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[DllImport(LIBNAME)]
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private static extern IntPtr features2d_SIFT_create_13(int nfeatures, int nOctaveLayers, double contrastThreshold);
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[DllImport(LIBNAME)]
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private static extern IntPtr features2d_SIFT_create_14(int nfeatures, int nOctaveLayers);
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[DllImport(LIBNAME)]
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private static extern IntPtr features2d_SIFT_create_15(int nfeatures);
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[DllImport(LIBNAME)]
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private static extern IntPtr features2d_SIFT_create_16();
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// C++: 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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[DllImport(LIBNAME)]
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private static extern IntPtr features2d_SIFT_create_17(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType, [MarshalAs(UnmanagedType.U1)] bool enable_precise_upscale);
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[DllImport(LIBNAME)]
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private static extern IntPtr features2d_SIFT_create_18(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType);
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// C++: String cv::SIFT::getDefaultName()
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[DllImport(LIBNAME)]
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private static extern IntPtr features2d_SIFT_getDefaultName_10(IntPtr nativeObj);
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// C++: void cv::SIFT::setNFeatures(int maxFeatures)
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[DllImport(LIBNAME)]
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private static extern void features2d_SIFT_setNFeatures_10(IntPtr nativeObj, int maxFeatures);
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// C++: int cv::SIFT::getNFeatures()
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[DllImport(LIBNAME)]
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private static extern int features2d_SIFT_getNFeatures_10(IntPtr nativeObj);
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// C++: void cv::SIFT::setNOctaveLayers(int nOctaveLayers)
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[DllImport(LIBNAME)]
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private static extern void features2d_SIFT_setNOctaveLayers_10(IntPtr nativeObj, int nOctaveLayers);
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// C++: int cv::SIFT::getNOctaveLayers()
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[DllImport(LIBNAME)]
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private static extern int features2d_SIFT_getNOctaveLayers_10(IntPtr nativeObj);
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// C++: void cv::SIFT::setContrastThreshold(double contrastThreshold)
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[DllImport(LIBNAME)]
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private static extern void features2d_SIFT_setContrastThreshold_10(IntPtr nativeObj, double contrastThreshold);
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// C++: double cv::SIFT::getContrastThreshold()
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[DllImport(LIBNAME)]
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private static extern double features2d_SIFT_getContrastThreshold_10(IntPtr nativeObj);
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// C++: void cv::SIFT::setEdgeThreshold(double edgeThreshold)
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[DllImport(LIBNAME)]
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private static extern void features2d_SIFT_setEdgeThreshold_10(IntPtr nativeObj, double edgeThreshold);
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// C++: double cv::SIFT::getEdgeThreshold()
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[DllImport(LIBNAME)]
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private static extern double features2d_SIFT_getEdgeThreshold_10(IntPtr nativeObj);
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// C++: void cv::SIFT::setSigma(double sigma)
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[DllImport(LIBNAME)]
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private static extern void features2d_SIFT_setSigma_10(IntPtr nativeObj, double sigma);
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// C++: double cv::SIFT::getSigma()
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[DllImport(LIBNAME)]
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private static extern double features2d_SIFT_getSigma_10(IntPtr nativeObj);
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// native support for java finalize()
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[DllImport(LIBNAME)]
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private static extern void features2d_SIFT_delete(IntPtr nativeObj);
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}
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}
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