0
votes

I am using OpenCV4Android for a project which involves both Java as well as C++ code. I am finding keypoints in an image using FAST feature detector using OpenCV's Java API. I need to pass its output (set of keypoints) which is a MatofKeypoint object in Java to a native C++ method. In the C++ method I need to use it as vector so that I can extract Keypoint descriptors form it.

I passed MatofObject form java and received it as a Mat& in C++, then manually tried to convert Mat& to vector by manually reading each point as described here. But the program crashes every time I access the received Mat& object with fatal signal 11,code 1.

I suspect the problem is due to difference in data structures used by C++ and Java API.

Any help will be appreciated, Thankyou!!!

In Java

public native void processImage(long matAddrTemplateKeypoints); // Native Method definition
FeatureDetector detector = FeatureDetector.create(FeatureDetector.FAST);
MatOfKeyPoint templateKeypoints = new MatOfKeyPoint();
detector.detect(img1, templateKeypoints);
processImage(templateKeypoints.getNativeObjAddr()); // Native method Call

In C++

JNIEXPORT void JNICALL MainActivity_processImage(JNIEnv*, jobject, jlong matAddrTemplateKeypoints)
Mat& templateKeypointMat = *(Mat*) matAddrTemplateKeypoints; // Casting received MatofPoint object as a Mat&

for(int i=0;i<templateKeypointMat.rows; i++){ // Code crashes here
...
}
1

1 Answers

0
votes

an answer was posted in the opencv-internal forum: http://answers.opencv.org/question/30869/how-to-pass-a-matofkeypoint-and-matofpoint2f-to-native-code-opencv-4-android/

Here is the code for KeyPoint and DMatch conversion:

// C++ / JNI
// vector_KeyPoint converters
using namespace cv;
using namespace std;

void Mat_to_vector_KeyPoint(Mat& mat, vector<KeyPoint>& v_kp)
{
    v_kp.clear();
    assert(mat.type()==CV_32FC(7) && mat.cols==1);
    for(int i=0; i<mat.rows; i++)
    {
        Vec<float, 7> v = mat.at< Vec<float, 7> >(i, 0);
        KeyPoint kp(v[0], v[1], v[2], v[3], v[4], (int)v[5], (int)v[6]);
        v_kp.push_back(kp);
    }
    return;
}

void Mat_to_vector_DMatch(Mat& mat, vector<DMatch>& v_dm)
{
    v_dm.clear();
    assert(mat.type()==CV_32FC(4) && mat.cols==1);
    for(int i=0; i<mat.rows; i++)
    {
        Vec<float, 4> v = mat.at< Vec<float, 4> >(i, 0);
        DMatch dm((int)v[0], (int)v[1], (int)v[2], v[3]);
        v_dm.push_back(dm);
    }
    return;
}

void Vector_KeyPoint_to_Mat(vector<KeyPoint>& v_kp, Mat& mat)
{
    int count = (int)v_kp.size();
    mat.create(count, 1, CV_32FC(7));
    for(int i=0; i<count; i++)
    {
        KeyPoint kp = v_kp[i];
        mat.at< Vec<float, 7> >(i, 0) = Vec<float, 7>(kp.pt.x, kp.pt.y, kp.size, kp.angle, kp.response, (float)kp.octave, (float)kp.class_id);
    }
}

void Vector_DMatch_to_Mat(vector<DMatch>& v_dm, Mat& mat)
{
    int count = (int)v_dm.size();
    mat.create(count, 1, CV_32FC(4));
    for(int i=0; i<count; i++)
    {
        DMatch dm = v_dm[i];
        mat.at< Vec<float, 4> >(i, 0) = Vec<float, 4>((float)dm.queryIdx, (float)dm.trainIdx, (float)dm.imgIdx, dm.distance);
    }
}

I just tried it on some examples and it worked for me very well.