Question

我正在尝试构建OpenCV附带的示例程序brief_match_test.cpp，但是当我运行程序时，我不断从cv :: findHomography（）函数中得到此错误：

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

我正在编译它：

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

我已经在程序中添加了一些内容来显示FAST算法找到的关键点，但是没有涉及处理单应性的部分。我将包括我修改过的例子，以防我搞砸了一些事情：

/*
 * 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;
}

Answer 1

我不确定，所以我真的回答这个问题只是因为到目前为止还没有其他人这么做，因为你问了这个问题已经有10个小时了。

我的第一个想法是你没有足够的点对。单应性需要至少4对，否则无法找到唯一的解决方案。如果匹配数量至少为4，您可能需要确保只调用findHomography。

或者，问题here和here是关于同一个失败的断言（虽然调用不同的函数引起的）。我猜测OpenCV会进行某种形式的动态类型检查或模板化，这样在编译时应该发生的类型不匹配错误最终会以失败的断言形式出现运行时错误。所有这些，也许你应该在传入findHomography之前将mpts_1和mpts_2转换为cv :: Mat。

Answer 2

这是内部的OpenCV类型问题。 findHomography（）想要vector＆lt; unsigned char＆gt;作为最后一个参数。但是drawMatches（）需要vector＆lt; char＆gt;作为最后一个。

Answer 3

我认为在this page上有很多关于brief_match_test.cpp以及纠正方法的解释。

Answer 4

您可以这样做：

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

OpenCV findHomography断言失败错误

4 个答案: