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OpenCV packaged with native libraries and loader for multiple platforms.
//
// This file is auto-generated. Please don't modify it!
//
package org.opencv.features2d;
import java.lang.String;
import java.util.List;
import org.opencv.core.Mat;
import org.opencv.core.MatOfKeyPoint;
import org.opencv.utils.Converters;
// C++: class javaFeatureDetector
/**
* Abstract base class for 2D image feature detectors.
*
* class CV_EXPORTS FeatureDetector
*
* // C++ code:
*
*
* public:
*
* virtual ~FeatureDetector();
*
* void detect(const Mat& image, vector& keypoints,
*
* const Mat& mask=Mat()) const;
*
* void detect(const vector& images,
*
* vector >& keypoints,
*
* const vector& masks=vector()) const;
*
* virtual void read(const FileNode&);
*
* virtual void write(FileStorage&) const;
*
* static Ptr create(const string& detectorType);
*
* protected:...
*
* };
*
* @see org.opencv.features2d.FeatureDetector : public Algorithm
*/
public class FeatureDetector {
protected final long nativeObj;
protected FeatureDetector(long addr) { nativeObj = addr; }
private static final int
GRIDDETECTOR = 1000,
PYRAMIDDETECTOR = 2000,
DYNAMICDETECTOR = 3000;
public static final int
FAST = 1,
STAR = 2,
SIFT = 3,
SURF = 4,
ORB = 5,
MSER = 6,
GFTT = 7,
HARRIS = 8,
SIMPLEBLOB = 9,
DENSE = 10,
BRISK = 11,
GRIDRETECTOR = 1000,
GRID_FAST = GRIDDETECTOR + FAST,
GRID_STAR = GRIDDETECTOR + STAR,
GRID_SIFT = GRIDDETECTOR + SIFT,
GRID_SURF = GRIDDETECTOR + SURF,
GRID_ORB = GRIDDETECTOR + ORB,
GRID_MSER = GRIDDETECTOR + MSER,
GRID_GFTT = GRIDDETECTOR + GFTT,
GRID_HARRIS = GRIDDETECTOR + HARRIS,
GRID_SIMPLEBLOB = GRIDDETECTOR + SIMPLEBLOB,
GRID_DENSE = GRIDDETECTOR + DENSE,
GRID_BRISK = GRIDDETECTOR + BRISK,
PYRAMID_FAST = PYRAMIDDETECTOR + FAST,
PYRAMID_STAR = PYRAMIDDETECTOR + STAR,
PYRAMID_SIFT = PYRAMIDDETECTOR + SIFT,
PYRAMID_SURF = PYRAMIDDETECTOR + SURF,
PYRAMID_ORB = PYRAMIDDETECTOR + ORB,
PYRAMID_MSER = PYRAMIDDETECTOR + MSER,
PYRAMID_GFTT = PYRAMIDDETECTOR + GFTT,
PYRAMID_HARRIS = PYRAMIDDETECTOR + HARRIS,
PYRAMID_SIMPLEBLOB = PYRAMIDDETECTOR + SIMPLEBLOB,
PYRAMID_DENSE = PYRAMIDDETECTOR + DENSE,
PYRAMID_BRISK = PYRAMIDDETECTOR + BRISK,
DYNAMIC_FAST = DYNAMICDETECTOR + FAST,
DYNAMIC_STAR = DYNAMICDETECTOR + STAR,
DYNAMIC_SIFT = DYNAMICDETECTOR + SIFT,
DYNAMIC_SURF = DYNAMICDETECTOR + SURF,
DYNAMIC_ORB = DYNAMICDETECTOR + ORB,
DYNAMIC_MSER = DYNAMICDETECTOR + MSER,
DYNAMIC_GFTT = DYNAMICDETECTOR + GFTT,
DYNAMIC_HARRIS = DYNAMICDETECTOR + HARRIS,
DYNAMIC_SIMPLEBLOB = DYNAMICDETECTOR + SIMPLEBLOB,
DYNAMIC_DENSE = DYNAMICDETECTOR + DENSE,
DYNAMIC_BRISK = DYNAMICDETECTOR + BRISK;
//
// C++: static javaFeatureDetector* javaFeatureDetector::create(int detectorType)
//
/**
* Creates a feature detector by its name.
*
* The following detector types are supported:
*
* -
"FAST" -- "FastFeatureDetector"
* -
"STAR" -- "StarFeatureDetector"
* -
"SIFT" -- "SIFT" (nonfree module)
* -
"SURF" -- "SURF" (nonfree module)
* -
"ORB" -- "ORB"
* -
"BRISK" -- "BRISK"
* -
"MSER" -- "MSER"
* -
"GFTT" -- "GoodFeaturesToTrackDetector"
* -
"HARRIS" -- "GoodFeaturesToTrackDetector" with Harris
* detector enabled
* -
"Dense" -- "DenseFeatureDetector"
* -
"SimpleBlob" -- "SimpleBlobDetector"
*
*
* Also a combined format is supported: feature detector adapter name
* ("Grid" -- "GridAdaptedFeatureDetector", "Pyramid"
* -- "PyramidAdaptedFeatureDetector") + feature detector name (see above), for
* example: "GridFAST", "PyramidSTAR".
*
* @param detectorType Feature detector type.
*
* @see org.opencv.features2d.FeatureDetector.create
*/
public static FeatureDetector create(int detectorType)
{
FeatureDetector retVal = new FeatureDetector(create_0(detectorType));
return retVal;
}
//
// C++: void javaFeatureDetector::detect(Mat image, vector_KeyPoint& keypoints, Mat mask = Mat())
//
/**
* Detects keypoints in an image (first variant) or image set (second variant).
*
* @param image Image.
* @param keypoints The detected keypoints. In the second variant of the method
* keypoints[i] is a set of keypoints detected in images[i].
* @param mask Mask specifying where to look for keypoints (optional). It must
* be a 8-bit integer matrix with non-zero values in the region of interest.
*
* @see org.opencv.features2d.FeatureDetector.detect
*/
public void detect(Mat image, MatOfKeyPoint keypoints, Mat mask)
{
Mat keypoints_mat = keypoints;
detect_0(nativeObj, image.nativeObj, keypoints_mat.nativeObj, mask.nativeObj);
return;
}
/**
* Detects keypoints in an image (first variant) or image set (second variant).
*
* @param image Image.
* @param keypoints The detected keypoints. In the second variant of the method
* keypoints[i] is a set of keypoints detected in images[i].
*
* @see org.opencv.features2d.FeatureDetector.detect
*/
public void detect(Mat image, MatOfKeyPoint keypoints)
{
Mat keypoints_mat = keypoints;
detect_1(nativeObj, image.nativeObj, keypoints_mat.nativeObj);
return;
}
//
// C++: void javaFeatureDetector::detect(vector_Mat images, vector_vector_KeyPoint& keypoints, vector_Mat masks = vector())
//
/**
* Detects keypoints in an image (first variant) or image set (second variant).
*
* @param images Image set.
* @param keypoints The detected keypoints. In the second variant of the method
* keypoints[i] is a set of keypoints detected in images[i].
* @param masks Masks for each input image specifying where to look for
* keypoints (optional). masks[i] is a mask for images[i].
*
* @see org.opencv.features2d.FeatureDetector.detect
*/
public void detect(List images, List keypoints, List masks)
{
Mat images_mat = Converters.vector_Mat_to_Mat(images);
Mat keypoints_mat = new Mat();
Mat masks_mat = Converters.vector_Mat_to_Mat(masks);
detect_2(nativeObj, images_mat.nativeObj, keypoints_mat.nativeObj, masks_mat.nativeObj);
Converters.Mat_to_vector_vector_KeyPoint(keypoints_mat, keypoints);
return;
}
/**
* Detects keypoints in an image (first variant) or image set (second variant).
*
* @param images Image set.
* @param keypoints The detected keypoints. In the second variant of the method
* keypoints[i] is a set of keypoints detected in images[i].
*
* @see org.opencv.features2d.FeatureDetector.detect
*/
public void detect(List images, List keypoints)
{
Mat images_mat = Converters.vector_Mat_to_Mat(images);
Mat keypoints_mat = new Mat();
detect_3(nativeObj, images_mat.nativeObj, keypoints_mat.nativeObj);
Converters.Mat_to_vector_vector_KeyPoint(keypoints_mat, keypoints);
return;
}
//
// C++: bool javaFeatureDetector::empty()
//
public boolean empty()
{
boolean retVal = empty_0(nativeObj);
return retVal;
}
//
// C++: void javaFeatureDetector::read(string fileName)
//
public void read(String fileName)
{
read_0(nativeObj, fileName);
return;
}
//
// C++: void javaFeatureDetector::write(string fileName)
//
public void write(String fileName)
{
write_0(nativeObj, fileName);
return;
}
@Override
protected void finalize() throws Throwable {
delete(nativeObj);
}
// C++: static javaFeatureDetector* javaFeatureDetector::create(int detectorType)
private static native long create_0(int detectorType);
// C++: void javaFeatureDetector::detect(Mat image, vector_KeyPoint& keypoints, Mat mask = Mat())
private static native void detect_0(long nativeObj, long image_nativeObj, long keypoints_mat_nativeObj, long mask_nativeObj);
private static native void detect_1(long nativeObj, long image_nativeObj, long keypoints_mat_nativeObj);
// C++: void javaFeatureDetector::detect(vector_Mat images, vector_vector_KeyPoint& keypoints, vector_Mat masks = vector())
private static native void detect_2(long nativeObj, long images_mat_nativeObj, long keypoints_mat_nativeObj, long masks_mat_nativeObj);
private static native void detect_3(long nativeObj, long images_mat_nativeObj, long keypoints_mat_nativeObj);
// C++: bool javaFeatureDetector::empty()
private static native boolean empty_0(long nativeObj);
// C++: void javaFeatureDetector::read(string fileName)
private static native void read_0(long nativeObj, String fileName);
// C++: void javaFeatureDetector::write(string fileName)
private static native void write_0(long nativeObj, String fileName);
// native support for java finalize()
private static native void delete(long nativeObj);
}