CODEWITHSUNDEEP
c++opencvopencv-stitching
Josh
Josh

Reputation: 1336

OpenCV findHomography assertion failed error

I'm trying to build the sample program brief_match_test.cpp that comes with OpenCV, but I keep getting this error from the cv::findHomography() function when I run the program:

OpenCV Error: Assertion failed (mtype == type0 || (CV_MAT_CN(mtype) == CV_MAT_CN(type0) && ((1 << type0) & fixedDepthMask) != 0)) in create, file /opt/local/var/macports/build/_opt_local_var_macports_sources_rsync.macports.org_release_tarballs_ports_graphics_opencv/opencv/work/OpenCV-2.4.3/modules/core/src/matrix.cpp, line 1421
libc++abi.dylib: terminate called throwing an exception
findHomography ... Abort trap: 6

I'm compiling it like this:

g++ `pkg-config --cflags opencv` `pkg-config --libs opencv` brief_match_test.cpp -o brief_match_test

I've added some stuff to the program to show the keypoints that the FAST algorithm finds, but haven't touched the section dealing with homography. I'll include my modified example just in case I did screw something up:

/*
 * matching_test.cpp
 *
 *  Created on: Oct 17, 2010
 *      Author: ethan
 */
#include "opencv2/core/core.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <vector>
#include <iostream>

using namespace cv;
using namespace std;

//Copy (x,y) location of descriptor matches found from KeyPoint data structures into Point2f vectors
static void matches2points(const vector<DMatch>& matches, const vector<KeyPoint>& kpts_train,
                    const vector<KeyPoint>& kpts_query, vector<Point2f>& pts_train, vector<Point2f>& pts_query)
{
  pts_train.clear();
  pts_query.clear();
  pts_train.reserve(matches.size());
  pts_query.reserve(matches.size());
  for (size_t i = 0; i < matches.size(); i++)
  {
    const DMatch& match = matches[i];
    pts_query.push_back(kpts_query[match.queryIdx].pt);
    pts_train.push_back(kpts_train[match.trainIdx].pt);
  }

}

static double match(const vector<KeyPoint>& /*kpts_train*/, const vector<KeyPoint>& /*kpts_query*/, DescriptorMatcher& matcher,
            const Mat& train, const Mat& query, vector<DMatch>& matches)
{

  double t = (double)getTickCount();
  matcher.match(query, train, matches); //Using features2d
  return ((double)getTickCount() - t) / getTickFrequency();
}

static void help()
{
       cout << "This program shows how to use BRIEF descriptor to match points in features2d" << endl <<
               "It takes in two images, finds keypoints and matches them displaying matches and final homography warped results" << endl <<
                "Usage: " << endl <<
                    "image1 image2 " << endl <<
                "Example: " << endl <<
                    "box.png box_in_scene.png " << endl;
}

const char* keys =
{
    "{1|  |box.png               |the first image}"
    "{2|  |box_in_scene.png|the second image}"
};

int main(int argc, const char ** argv)
{
    Mat outimg;
    help();
    CommandLineParser parser(argc, argv, keys);
    string im1_name = parser.get<string>("1");
    string im2_name = parser.get<string>("2");

    Mat im1 = imread(im1_name, CV_LOAD_IMAGE_GRAYSCALE);
    Mat im2 = imread(im2_name, CV_LOAD_IMAGE_GRAYSCALE);

    if (im1.empty() || im2.empty())
    {
      cout << "could not open one of the images..." << endl;
      cout << "the cmd parameters have next current value: " << endl;
      parser.printParams();
      return 1;
    }

    double t = (double)getTickCount();

    FastFeatureDetector detector(15);
    BriefDescriptorExtractor extractor(32); //this is really 32 x 8 matches since they are binary matches packed into bytes

    vector<KeyPoint> kpts_1, kpts_2;
    detector.detect(im1, kpts_1);
    detector.detect(im2, kpts_2);

    t = ((double)getTickCount() - t) / getTickFrequency();

    cout << "found " << kpts_1.size() << " keypoints in " << im1_name << endl << "fount " << kpts_2.size()
        << " keypoints in " << im2_name << endl << "took " << t << " seconds." << endl;

    drawKeypoints(im1, kpts_1, outimg, 200);
    imshow("Keypoints - Image1", outimg);
    drawKeypoints(im2, kpts_2, outimg, 200);
    imshow("Keypoints - Image2", outimg);

    Mat desc_1, desc_2;

    cout << "computing descriptors..." << endl;

    t = (double)getTickCount();

    extractor.compute(im1, kpts_1, desc_1);
    extractor.compute(im2, kpts_2, desc_2);

    t = ((double)getTickCount() - t) / getTickFrequency();

    cout << "done computing descriptors... took " << t << " seconds" << endl;

    //Do matching using features2d
    cout << "matching with BruteForceMatcher<Hamming>" << endl;
    BFMatcher matcher_popcount(NORM_HAMMING);
    vector<DMatch> matches_popcount;
    double pop_time = match(kpts_1, kpts_2, matcher_popcount, desc_1, desc_2, matches_popcount);
    cout << "done BruteForceMatcher<Hamming> matching. took " << pop_time << " seconds" << endl;

    vector<Point2f> mpts_1, mpts_2;
    cout << "matches2points ... ";
    matches2points(matches_popcount, kpts_1, kpts_2, mpts_1, mpts_2); //Extract a list of the (x,y) location of the matches
    cout << "done" << endl;

    vector<char> outlier_mask;
    cout << "findHomography ... ";
    Mat H = findHomography(mpts_2, mpts_1, RANSAC, 1, outlier_mask);
    cout << "done" << endl;

    cout << "drawMatches ... ";
    drawMatches(im2, kpts_2, im1, kpts_1, matches_popcount, outimg, Scalar::all(-1), Scalar::all(-1), outlier_mask);
    cout << "done" << endl;
    imshow("matches - popcount - outliers removed", outimg);

    Mat warped;
    Mat diff;
    warpPerspective(im2, warped, H, im1.size());
    imshow("warped", warped);
    absdiff(im1,warped,diff);
    imshow("diff", diff);
    waitKey();
    return 0;
}

Upvotes: 2

Views: 3434

Answers (4)

Dongguadedidi
Dongguadedidi

Reputation: 1

You can do like this:

vector<char> outlier_mask; Mat outlier(outlier_mask); Mat H = findHomography(mpts_2, mpts_1, RANSAC, 1, outlier);

Upvotes: 0

Giuseppe Dini
Giuseppe Dini

Reputation: 762

I think that on this page a lot of things are explained about brief_match_test.cpp and the ways to correct it.

Upvotes: 0

svv
svv

Reputation: 11

It's internal OpenCV types problem. findHomography() wants vector < unsigned char > as the last parameter. But drawMatches() requires vector < char > as last one.

Upvotes: 1

maditya
maditya

Reputation: 8886

I don't know for sure, so I'm really answering this just because no one else has so far and it's been 10 hours since you asked the question.

My first thought is that you don't have enough point pairs. A homography requires at least 4 pairs, otherwise a unique solution cannot be found. You may want to make sure that you only call findHomography if the number of matches is at least 4.

Alternatively, the questions here and here are about the same failed assertion (caused by calling different functions than yours, though). I'm guessing OpenCV does some form of dynamic type checking or templating such that a type mismatch error that ought to occur at compile time ends up being a run-time error in the form of a failed assertion. All this to say, maybe you should convert mpts_1 and mpts_2 to cv::Mat before passing in to findHomography.

Upvotes: 1

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