Hi !
I'm following the tutorial : http://docs.opencv.org/3.0-beta/doc/tutorials/features2d/akaze_matching/akaze_matching.html
I'm on Debian.
The compilation is good, I had an error on matmul, I modified the file to avoid it.
And now when I launch, I have the error :
> libdc1394 error: Failed to initialize libdc1394
OpenCV Error: Assertion failed (scn == 3 || scn == 4) in cvtColor, file /root/Downloads/opencv-3.0.0/modules/imgproc/src/color.cpp, line 7564
terminate called after throwing an instance of 'cv::Exception'
what(): /root/
donwloads/opencv-3.0.0/modules/imgproc/src/color.cpp:7564: error: (-215) scn == 3 || scn == 4 in function cvtColor> Aborted
I don't know why I have it so I post my code.
#include
#include
#include
#include
#include
using namespace std;
using namespace cv;
const float inlier_threshold = 2.5f; // Distance threshold to identify inliers
const float nn_match_ratio = 0.8f; // Nearest neighbor matching ratio
int main(void)
{
Mat img1 = imread("lena.png");
Mat img2 = imread("lena2.png");
Mat grayimage1;
Mat grayimage2;
cvtColor(img1, grayimage1, COLOR_BGR2GRAY);
cvtColor(img2, grayimage2, COLOR_BGR2GRAY);
img1 = grayimage1;
img2 = grayimage2;
img1.convertTo(img1, CV_32F);
img2.convertTo(img2, CV_32F);
Mat homography;
FileStorage fs("./match.xml", FileStorage::READ);
fs.getFirstTopLevelNode() >> homography;
vector kpts1, kpts2;
Mat desc1, desc2;
Ptr akaze = AKAZE::create();
akaze->detectAndCompute(img1, noArray(), kpts1, desc1);
akaze->detectAndCompute(img2, noArray(), kpts2, desc2);
BFMatcher matcher(NORM_HAMMING);
vector< vector> nn_matches;
matcher.knnMatch(desc1, desc2, nn_matches, 2);
vector matched1, matched2, inliers1, inliers2;
vector good_matches;
for(size_t i = 0; i < nn_matches.size(); i++) {
DMatch first = nn_matches[i][0];
float dist1 = nn_matches[i][0].distance;
float dist2 = nn_matches[i][1].distance;
if(dist1 < nn_match_ratio * dist2) {
matched1.push_back(kpts1[first.queryIdx]);
matched2.push_back(kpts2[first.trainIdx]);
}
}
for(unsigned i = 0; i < matched1.size(); i++) {
Mat col = Mat::ones(3, 1, CV_32F);
col.at(0) = matched1[i].pt.x;
col.at(1) = matched1[i].pt.y;
col = homography * col;
col /= col.at(2);
double dist = sqrt( pow(col.at(0) - matched2[i].pt.x, 2) +
pow(col.at(1) - matched2[i].pt.y, 2));
if(dist < inlier_threshold) {
int new_i = static_cast(inliers1.size());
inliers1.push_back(matched1[i]);
inliers2.push_back(matched2[i]);
good_matches.push_back(DMatch(new_i, new_i, 0));
}
}
Mat res;
drawMatches(img1, inliers1, img2, inliers2, good_matches, res);
imwrite("res.png", res);
double inlier_ratio = inliers1.size() * 1.0 / matched1.size();
cout << "A-KAZE Matching Results" << endl;
cout << "*******************************" << endl;
cout << "# Keypoints 1: \t" << kpts1.size() << endl;
cout << "# Keypoints 2: \t" << kpts2.size() << endl;
cout << "# Matches: \t" << matched1.size() << endl;
cout << "# Inliers: \t" << inliers1.size() << endl;
cout << "# Inliers Ratio: \t" << inlier_ratio << endl;
cout << endl;
return 0;
}
Thank you for your help.