java调用opencv的sift方法

代码找了好多，但是没有java版本的

public static void TestSift(Mat image1,Mat image2) {
Mat clone1=image1.clone();
Mat src1=image1.clone();

Mat clone2=image2.clone();
Mat src2=image2.clone();

Imgproc.GaussianBlur(clone1, clone1, new Size(3, 3), 0, 0);
Imgproc.cvtColor(clone1, clone1,Imgproc.COLOR_BGR2GRAY);

Imgproc.GaussianBlur(clone2, clone2, new Size(3, 3), 0, 0);
Imgproc.cvtColor(clone2, clone2,Imgproc.COLOR_BGR2GRAY);

MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
Mat des1=new Mat();
Mat des2=new Mat();
//	匹配的点数
SIFT sift=SIFT.create(200);
	//提取对象关键点
//	sift.detect(clone1,keypoints1);
//	sift.detect(clone2,keypoints2);
	//提取描述子
//	sift.compute(clone1,keypoints1, des1);
//	sift.compute(clone2,keypoints2, des2);
	
sift.detectAndCompute(clone1, new Mat(), keypoints1, des1);
sift.detectAndCompute(clone2, new Mat(), keypoints2, des2);

MatOfDMatch md=new  MatOfDMatch();
FlannBasedMatcher matcher=FlannBasedMatcher.create();

matcher.match(des1, des2, md);

double maxDist = 0;
double minDist = 50;

DMatch[] mats = md.toArray();
List<DMatch> bestMatches= new ArrayList<DMatch>();

for (int i = 0; i < mats.length; i++) {
	double dist = mats[i].distance;
	if (dist < minDist) {
		minDist = dist;
	}
	if (dist > maxDist) {
		maxDist = dist;
	}
}
System.out.println("max_dist : "+maxDist);
System.out.println("min_dist : "+minDist);

double threshold = 3 * minDist;
double threshold2 = 2 * minDist;

if (threshold2 >= maxDist){
    threshold = minDist * 1.1;
}
else if (threshold >= maxDist){
    threshold = threshold2 * 1.4;
}

if(0d==threshold) {
	threshold=0.3*maxDist;
}

System.out.println("Threshold : "+threshold);

for (int i = 0; i < mats.length; i++)
{
	//distance越小,代表DMatch的匹配率越高,
    Double dist = (double) mats[i].distance;
    System.out.println(String.format(i + " match distance best : %s", dist));
    if (dist <= threshold)
    {
        bestMatches.add(mats[i]);
        System.out.println(String.format(i + " best match added : %s", dist));
    }
}
md.fromList(bestMatches);
Mat result=new Mat();
Features2d.drawMatches(src1, keypoints1, src2, keypoints2, md, result);
HighGui.imshow("SIFT", result);
}

knn写法

public static void TestSiftKnn(Mat image1,Mat image2) {
	//FastFeatureDetector detector = FastFeatureDetector.create(FastFeatureDetector.FAST_N);
	Mat clone1=image1.clone();
	Mat src1=image1.clone();
	
	Mat clone2=image2.clone();
	Mat src2=image2.clone();

	Imgproc.GaussianBlur(clone1, clone1, new Size(3, 3), 0, 0);
	Imgproc.cvtColor(clone1, clone1,Imgproc.COLOR_BGR2GRAY);
	
	Imgproc.GaussianBlur(clone2, clone2, new Size(3, 3), 0, 0);
	Imgproc.cvtColor(clone2, clone2,Imgproc.COLOR_BGR2GRAY);
	
	MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
	MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
	Mat des1=new Mat();
	Mat des2=new Mat();
	SIFT sift=SIFT.create(200);
	//提取对象关键点
//	sift.detect(clone1,keypoints1);
//	sift.detect(clone2,keypoints2);
	//提取描述子
//	sift.compute(clone1,keypoints1, des1);
//	sift.compute(clone2,keypoints2, des2);
	
	sift.detectAndCompute(clone1, new Mat(), keypoints1, des1);
	sift.detectAndCompute(clone2, new Mat(), keypoints2, des2);
	
	MatOfDMatch md=new  MatOfDMatch();
	FlannBasedMatcher matcher=FlannBasedMatcher.create();
	
	//matcher.match(des1, des2, md);
	
	List<Mat> matList=new ArrayList<Mat>();
	List<MatOfDMatch> mdList=new ArrayList<MatOfDMatch>();
	matList.add(des1);
	
    matcher.add(matList);
    matcher.train();
    
    matcher.knnMatch(des2, mdList, 2);
    
    List<DMatch> dMatchList = new ArrayList<DMatch>();
    Iterator<MatOfDMatch> ite=mdList.iterator();
    while(ite.hasNext()) {
    	MatOfDMatch next=ite.next();
    	if (next.toArray()[0].distance < 0.2 * next.toArray()[1].distance) {
    		System.out.println(next.toArray()[0].distance+"->"+next.toArray()[1].distance);
    		dMatchList.add(next.toArray()[0]);
    	}else {
    		ite.remove();
    	}
    }
   md.fromList(dMatchList);
    
	Mat result=new Mat();
//	Features2d.drawMatches(src1, keypoints1, src2, keypoints2, md, result);
	Features2d.drawMatchesKnn(src1, keypoints1, src2, keypoints2, mdList, result);
	HighGui.imshow("SIFT", result);
}