Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D. Lowe [Lowe04] .
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override string | getDefaultName () |
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void | setNFeatures (int maxFeatures) |
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int | getNFeatures () |
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void | setNOctaveLayers (int nOctaveLayers) |
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int | getNOctaveLayers () |
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void | setContrastThreshold (double contrastThreshold) |
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double | getContrastThreshold () |
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void | setEdgeThreshold (double edgeThreshold) |
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double | getEdgeThreshold () |
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void | setSigma (double sigma) |
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double | getSigma () |
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void | detect (Mat image, MatOfKeyPoint keypoints, Mat mask) |
| Detects keypoints in an image (first variant) or image set (second variant). More...
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void | detect (Mat image, MatOfKeyPoint keypoints) |
| Detects keypoints in an image (first variant) or image set (second variant). More...
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void | detect (List< Mat > images, List< MatOfKeyPoint > keypoints, List< Mat > masks) |
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void | detect (List< Mat > images, List< MatOfKeyPoint > keypoints) |
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void | compute (Mat image, MatOfKeyPoint keypoints, Mat descriptors) |
| Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant). More...
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void | compute (List< Mat > images, List< MatOfKeyPoint > keypoints, List< Mat > descriptors) |
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void | detectAndCompute (Mat image, Mat mask, MatOfKeyPoint keypoints, Mat descriptors, bool useProvidedKeypoints) |
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void | detectAndCompute (Mat image, Mat mask, MatOfKeyPoint keypoints, Mat descriptors) |
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int | descriptorSize () |
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int | descriptorType () |
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int | defaultNorm () |
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void | write (string fileName) |
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void | read (string fileName) |
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override bool | empty () |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...
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IntPtr | getNativeObjAddr () |
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virtual void | clear () |
| Clears the algorithm state. More...
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void | save (string filename) |
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void | Dispose () |
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void | ThrowIfDisposed () |
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static new SIFT | __fromPtr__ (IntPtr addr) |
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static SIFT | create (int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, bool enable_precise_upscale) |
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static SIFT | create (int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma) |
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static SIFT | create (int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold) |
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static SIFT | create (int nfeatures, int nOctaveLayers, double contrastThreshold) |
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static SIFT | create (int nfeatures, int nOctaveLayers) |
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static SIFT | create (int nfeatures) |
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static SIFT | create () |
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static SIFT | create (int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType, bool enable_precise_upscale) |
| Create SIFT with specified descriptorType. More...
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static SIFT | create (int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType) |
| Create SIFT with specified descriptorType. More...
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static new Feature2D | __fromPtr__ (IntPtr addr) |
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static Algorithm | __fromPtr__ (IntPtr addr) |
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static IntPtr | ThrowIfNullIntPtr (IntPtr ptr) |
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Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D. Lowe [Lowe04] .
◆ __fromPtr__()
static new SIFT OpenCVForUnity.Features2dModule.SIFT.__fromPtr__ |
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IntPtr |
addr | ) |
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static |
◆ create() [1/9]
static SIFT OpenCVForUnity.Features2dModule.SIFT.create |
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int |
nfeatures, |
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int |
nOctaveLayers, |
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double |
contrastThreshold, |
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double |
edgeThreshold, |
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double |
sigma, |
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bool |
enable_precise_upscale |
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) |
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static |
- Parameters
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nfeatures | The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast) |
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. |
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. |
- Note
- The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.
- Parameters
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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). |
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. |
enable_precise_upscale | Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default. |
◆ create() [2/9]
static SIFT OpenCVForUnity.Features2dModule.SIFT.create |
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int |
nfeatures, |
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int |
nOctaveLayers, |
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double |
contrastThreshold, |
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double |
edgeThreshold, |
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double |
sigma |
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) |
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static |
- Parameters
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nfeatures | The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast) |
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. |
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. |
- Note
- The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.
- Parameters
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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). |
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. |
enable_precise_upscale | Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default. |
◆ create() [3/9]
static SIFT OpenCVForUnity.Features2dModule.SIFT.create |
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int |
nfeatures, |
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int |
nOctaveLayers, |
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double |
contrastThreshold, |
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double |
edgeThreshold |
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) |
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static |
- Parameters
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nfeatures | The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast) |
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. |
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. |
- Note
- The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.
- Parameters
-
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). |
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. |
enable_precise_upscale | Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default. |
◆ create() [4/9]
static SIFT OpenCVForUnity.Features2dModule.SIFT.create |
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int |
nfeatures, |
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int |
nOctaveLayers, |
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double |
contrastThreshold |
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) |
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static |
- Parameters
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nfeatures | The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast) |
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. |
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. |
- Note
- The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.
- Parameters
-
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). |
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. |
enable_precise_upscale | Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default. |
◆ create() [5/9]
static SIFT OpenCVForUnity.Features2dModule.SIFT.create |
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int |
nfeatures, |
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int |
nOctaveLayers |
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) |
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static |
- Parameters
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nfeatures | The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast) |
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. |
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. |
- Note
- The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.
- Parameters
-
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). |
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. |
enable_precise_upscale | Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default. |
◆ create() [6/9]
static SIFT OpenCVForUnity.Features2dModule.SIFT.create |
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int |
nfeatures | ) |
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static |
- Parameters
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nfeatures | The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast) |
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. |
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. |
- Note
- The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.
- Parameters
-
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). |
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. |
enable_precise_upscale | Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default. |
◆ create() [7/9]
static SIFT OpenCVForUnity.Features2dModule.SIFT.create |
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| ) |
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static |
- Parameters
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nfeatures | The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast) |
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. |
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. |
- Note
- The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.
- Parameters
-
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). |
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. |
enable_precise_upscale | Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default. |
◆ create() [8/9]
static SIFT OpenCVForUnity.Features2dModule.SIFT.create |
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int |
nfeatures, |
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int |
nOctaveLayers, |
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double |
contrastThreshold, |
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double |
edgeThreshold, |
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double |
sigma, |
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int |
descriptorType, |
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bool |
enable_precise_upscale |
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) |
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static |
Create SIFT with specified descriptorType.
- Parameters
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nfeatures | The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast) |
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. |
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. |
- Note
- The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.
- Parameters
-
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). |
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. |
descriptorType | The type of descriptors. Only CV_32F and CV_8U are supported. |
enable_precise_upscale | Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default. |
◆ create() [9/9]
static SIFT OpenCVForUnity.Features2dModule.SIFT.create |
( |
int |
nfeatures, |
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int |
nOctaveLayers, |
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double |
contrastThreshold, |
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double |
edgeThreshold, |
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double |
sigma, |
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int |
descriptorType |
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) |
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static |
Create SIFT with specified descriptorType.
- Parameters
-
nfeatures | The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast) |
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. |
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. |
- Note
- The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.
- Parameters
-
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). |
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. |
descriptorType | The type of descriptors. Only CV_32F and CV_8U are supported. |
enable_precise_upscale | Whether to enable precise upscaling in the scale pyramid, which maps index \(\texttt{x}\) to \(\texttt{2x}\). This prevents localization bias. The option is disabled by default. |
◆ Dispose()
override void OpenCVForUnity.Features2dModule.SIFT.Dispose |
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bool |
disposing | ) |
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protectedvirtual |
◆ getContrastThreshold()
double OpenCVForUnity.Features2dModule.SIFT.getContrastThreshold |
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◆ getDefaultName()
override string OpenCVForUnity.Features2dModule.SIFT.getDefaultName |
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virtual |
◆ getEdgeThreshold()
double OpenCVForUnity.Features2dModule.SIFT.getEdgeThreshold |
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◆ getNFeatures()
int OpenCVForUnity.Features2dModule.SIFT.getNFeatures |
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◆ getNOctaveLayers()
int OpenCVForUnity.Features2dModule.SIFT.getNOctaveLayers |
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◆ getSigma()
double OpenCVForUnity.Features2dModule.SIFT.getSigma |
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◆ setContrastThreshold()
void OpenCVForUnity.Features2dModule.SIFT.setContrastThreshold |
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double |
contrastThreshold | ) |
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◆ setEdgeThreshold()
void OpenCVForUnity.Features2dModule.SIFT.setEdgeThreshold |
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double |
edgeThreshold | ) |
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◆ setNFeatures()
void OpenCVForUnity.Features2dModule.SIFT.setNFeatures |
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int |
maxFeatures | ) |
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◆ setNOctaveLayers()
void OpenCVForUnity.Features2dModule.SIFT.setNOctaveLayers |
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int |
nOctaveLayers | ) |
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◆ setSigma()
void OpenCVForUnity.Features2dModule.SIFT.setSigma |
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double |
sigma | ) |
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The documentation for this class was generated from the following file:
- OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/features2d/SIFT.cs