org.opencv.features2d.SIFT Maven / Gradle / Ivy
//
// This file is auto-generated. Please don't modify it!
//
package org.opencv.features2d;
import org.opencv.features2d.Feature2D;
import org.opencv.features2d.SIFT;
// C++: class SIFT
/**
* Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform
* (SIFT) algorithm by D. Lowe CITE: Lowe04 .
*/
public class SIFT extends Feature2D {
protected SIFT(long addr) { super(addr); }
// internal usage only
public static SIFT __fromPtr__(long addr) { return new SIFT(addr); }
//
// C++: static Ptr_SIFT cv::SIFT::create(int nfeatures = 0, int nOctaveLayers = 3, double contrastThreshold = 0.04, double edgeThreshold = 10, double sigma = 1.6)
//
/**
* @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.
*
* 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.
*
* @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.
* @return automatically generated
*/
public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma) {
return SIFT.__fromPtr__(create_0(nfeatures, nOctaveLayers, contrastThreshold, edgeThreshold, sigma));
}
/**
* @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.
*
* 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.
*
* @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).
*
* 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, double edgeThreshold) {
return SIFT.__fromPtr__(create_1(nfeatures, nOctaveLayers, contrastThreshold, edgeThreshold));
}
/**
* @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.
*
* 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.
*
* 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__(create_2(nfeatures, nOctaveLayers, contrastThreshold));
}
/**
* @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.
*
* 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.
*
* 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__(create_3(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)
*
* 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.
*
* 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.
*
* 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__(create_4(nfeatures));
}
/**
* (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.
*
* 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.
*
* 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__(create_5());
}
//
// C++: String cv::SIFT::getDefaultName()
//
public String getDefaultName() {
return getDefaultName_0(nativeObj);
}
@Override
protected void finalize() throws Throwable {
delete(nativeObj);
}
// C++: static Ptr_SIFT cv::SIFT::create(int nfeatures = 0, int nOctaveLayers = 3, double contrastThreshold = 0.04, double edgeThreshold = 10, double sigma = 1.6)
private static native long create_0(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma);
private static native long create_1(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold);
private static native long create_2(int nfeatures, int nOctaveLayers, double contrastThreshold);
private static native long create_3(int nfeatures, int nOctaveLayers);
private static native long create_4(int nfeatures);
private static native long create_5();
// C++: String cv::SIFT::getDefaultName()
private static native String getDefaultName_0(long nativeObj);
// native support for java finalize()
private static native void delete(long nativeObj);
}
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