void DoProcess()
{
if (!(owner.Value is OpenCVForUnityPlayMakerActions.SIFT))
{
LogError("owner is not initialized. Add Action \"newSIFT\".");
return;
}
OpenCVForUnity.Features2dModule.SIFT wrapped_owner = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.SIFT, OpenCVForUnity.Features2dModule.SIFT>(owner);
storeResult.Value = wrapped_owner.getDefaultName();
}
//
// C++: static Ptr_SIFT cv::SIFT::create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType)
//
/**
* Create SIFT with specified descriptorType.
* param nfeatures The number of best features to retain. The features are ranked by their scores
* (measured in SIFT algorithm as the local contrast)
*
* param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
* number of octaves is computed automatically from the image resolution.
*
* param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
*
* <b>Note:</b> 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.
*
* param edgeThreshold The threshold used to filter out edge-like features. Note that the its meaning
* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
* filtered out (more features are retained).
*
* param sigma The sigma of the Gaussian applied to the input image at the octave \#0. If your image
* is captured with a weak camera with soft lenses, you might want to reduce the number.
*
* param descriptorType The type of descriptors. Only CV_32F and CV_8U are supported.
* return automatically generated
*/
public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType)
{
return(SIFT.__fromPtr__(features2d_SIFT_create_10(nfeatures, nOctaveLayers, contrastThreshold, edgeThreshold, sigma, descriptorType)));
}
/**
* (measured in SIFT algorithm as the local contrast)
*
* number of octaves is computed automatically from the image resolution.
*
* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
*
* <b>Note:</b> 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.
*
* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
* filtered out (more features are retained).
*
* is captured with a weak camera with soft lenses, you might want to reduce the number.
* return automatically generated
*/
public static SIFT create()
{
return(SIFT.__fromPtr__(features2d_SIFT_create_16()));
}
/**
* param nfeatures The number of best features to retain. The features are ranked by their scores
* (measured in SIFT algorithm as the local contrast)
*
* number of octaves is computed automatically from the image resolution.
*
* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
*
* <b>Note:</b> 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.
*
* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
* filtered out (more features are retained).
*
* is captured with a weak camera with soft lenses, you might want to reduce the number.
* return automatically generated
*/
public static SIFT create(int nfeatures)
{
return(SIFT.__fromPtr__(features2d_SIFT_create_15(nfeatures)));
}
/**
* param nfeatures The number of best features to retain. The features are ranked by their scores
* (measured in SIFT algorithm as the local contrast)
*
* param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
* number of octaves is computed automatically from the image resolution.
*
* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
*
* <b>Note:</b> 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.
*
* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
* filtered out (more features are retained).
*
* is captured with a weak camera with soft lenses, you might want to reduce the number.
* return automatically generated
*/
public static SIFT create(int nfeatures, int nOctaveLayers)
{
return(SIFT.__fromPtr__(features2d_SIFT_create_14(nfeatures, nOctaveLayers)));
}
/**
* param nfeatures The number of best features to retain. The features are ranked by their scores
* (measured in SIFT algorithm as the local contrast)
*
* param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
* number of octaves is computed automatically from the image resolution.
*
* param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
* (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
*
* <b>Note:</b> 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.
*
* is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
* filtered out (more features are retained).
*
* is captured with a weak camera with soft lenses, you might want to reduce the number.
* return automatically generated
*/
public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold)
{
return(SIFT.__fromPtr__(features2d_SIFT_create_13(nfeatures, nOctaveLayers, contrastThreshold)));
}
public SIFT(OpenCVForUnity.Features2dModule.SIFT nativeObj) : base(nativeObj)
{
}