检测图像关键点--javaCV --EXCEPTION_ACCESS_VIOLATION

问题描述

我是java开发人员。我的目标是使用javaCV检测图像关键点

I'm java developer .My goal is to detect image keypoints using javaCV

这是我的代码：

      final CvMat image1 = cvLoadImageM("im1.png" , 0);

      final CvMat image2 = cvLoadImageM("im2.png", 0);

      SIFT  sift = new SIFT();

  FeatureDetector featureDetector =sift.getFeatureDetector();


      KeyPoint keypoint1 = new KeyPoint();

  KeyPoint keypoint2 = new KeyPoint() ;

  featureDetector.detect(image1, keypoint1 , null);


      featureDetector.detect(image2,keypoint2, null);

但是当我运行此代码时，我遇到了访问冲突异常

but when I run this code I got an access violation exception

     A fatal error has been detected by the Java Runtime Environment:

     EXCEPTION_ACCESS_VIOLATION (0xc0000005) at pc=0x7795e3be, pid=128, tid=2348


     JRE version: Java(TM) SE Runtime Environment (7.0_45-b18) (build 1.7.0_45-b18)

     Java VM: Java HotSpot(TM) Client VM (24.45-b08 mixed mode, sharing windows-x86 )

     Problematic frame:

     C  [ntdll.dll+0x2e3be]

我看不出问题出在哪里？

I can't see where is the problem ?

推荐答案

你的代码对我有用;我唯一改变的是：

Your code worked for me; the only thing I have changed is:

final CvMat image1 = cvLoadImageM("C:/temp/316.jpg" , 0);
final CvMat image2 = cvLoadImageM("C:/temp/330.jpg", 0);

检查您的图片路径：

import com.googlecode.javacv.cpp.opencv_core.CvMat;
import com.googlecode.javacv.cpp.opencv_features2d.FeatureDetector;
import com.googlecode.javacv.cpp.opencv_features2d.KeyPoint;
import com.googlecode.javacv.cpp.opencv_nonfree.SIFT;

import static com.googlecode.javacv.cpp.opencv_highgui.cvLoadImageM;
public class any {
public static void main(String args[])
{
final CvMat image1 = cvLoadImageM("C:/temp/316.jpg" , 0);

    final CvMat image2 = cvLoadImageM("C:/temp/330.jpg", 0);
    if(image1==null)
    System.out.println("image is null");
if(image2==null)
    System.out.println("image is null");

SIFT  sift = new SIFT();
FeatureDetector featureDetector =sift.getFeatureDetector();
KeyPoint keypoint1 = new KeyPoint();
KeyPoint keypoint2 = new KeyPoint() ;
featureDetector.detect(image1, keypoint1 , null);
featureDetector.detect(image2,keypoint2, null);
System.out.println(keypoint1);
}
}

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