在编译我在互联网上找到的代码时，我遇到了堆损坏异常。我是初学者，我不知道如何解决问题。 异常发生在以下行：
matcher.knnMatch(desObject, des_image, matches, 2);
有人能告诉我应该用这行代码代替什么？
完整的源代码：
cv::initModule_nonfree();
// turn performance analysis functions on if testing = true
bool testing = false;
double t; // timing variable
// load training image
Mat object = imread("boo2.png", CV_LOAD_IMAGE_GRAYSCALE);
if (!object.data) {
cout << "Can't open image";
return -1;
}
namedWindow("Good Matches", CV_WINDOW_AUTOSIZE);
// SURF Detector, and descriptor parameters
int minHess = 3000;
vector<KeyPoint> kpObject, kpImage;
Mat desObject, desImage;
// Performance measures calculations for report
if (testing) {
cout << object.rows << " " << object.cols << endl;
// calculate integral image
Mat iObject;
integral(object, iObject);
imshow("Good Matches", iObject);
imwrite("boo2.png", iObject);
cvWaitKey(0);
// calculate number of interest points, computation time as f(minHess)
int minHessVector[] = {100, 500, 1000, 1500, 2000, 2500, 3000,
3500, 4000, 4500, 5000, 5500, 6000, 6500,
7000, 7500, 8000, 8500, 9000, 9500, 10000};
int minH;
std::ofstream file;
file.open("C:/School/Image Processing/TimingC.csv", std::ofstream::out);
for (int i = 0; i < 20; i++) {
minH = minHessVector[i];
t = (double)getTickCount();
SurfFeatureDetector detector(minH);
detector.detect(object, kpObject);
t = ((double)getTickCount() - t) / getTickFrequency();
file << minHess << "," << kpObject.size() << "," << t << ",";
cout << t << " " << kpObject.size() << " " << desObject.size() << endl;
t = (double)getTickCount();
SurfDescriptorExtractor extractor;
extractor.compute(object, kpObject, desObject);
t = ((double)getTickCount() - t) / getTickFrequency();
file << t << endl;
}
file.close();
// Display keypoints on training image
Mat interestPointObject = object;
for (unsigned int i = 0; i < kpObject.size(); i++) {
if (kpObject[i].octave) {
circle(interestPointObject, kpObject[i].pt, kpObject[i].size, 0);
string octaveS;
switch (kpObject[i].octave) {
case 0:
octaveS = "0";
break;
case 1:
octaveS = '1';
break;
case 2:
octaveS = '2';
break;
default:
break;
}
putText(interestPointObject, octaveS, kpObject[i].pt,
FONT_HERSHEY_COMPLEX_SMALL, 1, cvScalar(0, 0, 250), 1, CV_AA);
}
}
imshow("Good Matches", interestPointObject);
imwrite("C:/School/Image Processing/bookIP2.jpg", interestPointObject);
cvWaitKey(0);
}
// SURF Detector, and descriptor parameters, match object
// initialization
minHess = 2000;
SurfFeatureDetector detector(minHess);
detector.detect(object, kpObject);
SurfDescriptorExtractor extractor;
extractor.compute(object, kpObject, desObject);
FlannBasedMatcher matcher;
// Initialize video and display window
VideoCapture cap(1); // camera 1 is webcam
if (!cap.isOpened()) return -1;
// Object corner points for plotting box
vector<Point2f> obj_corners(4);
obj_corners[0] = cvPoint(0, 0);
obj_corners[1] = cvPoint(object.cols, 0);
obj_corners[2] = cvPoint(object.cols, object.rows);
obj_corners[3] = cvPoint(0, object.rows);
// video loop
char escapeKey = 'k';
double frameCount = 0;
float thresholdMatchingNN = 0.7;
unsigned int thresholdGoodMatches = 4;
unsigned int thresholdGoodMatchesV[] = {4, 5, 6, 7, 8, 9, 10};
for (int j = 0; j < 7; j++) {
thresholdGoodMatches = thresholdGoodMatchesV[j];
// thresholdGoodMatches=8;
cout << thresholdGoodMatches << endl;
if (true) {
t = (double)getTickCount();
}
while (escapeKey != 'q') {
frameCount++;
Mat frame;
Mat image;
cap >> frame;
cvtColor(frame, image, CV_RGB2GRAY);
Mat des_image, img_matches, H;
vector<KeyPoint> kp_image;
vector<vector<DMatch>> matches;
vector<DMatch> good_matches;
vector<Point2f> obj;
vector<Point2f> scene;
vector<Point2f> scene_corners(4);
detector.detect(image, kp_image);
extractor.compute(image, kp_image, des_image);
matcher.knnMatch(desObject, des_image, matches, 2);
for (int i = 0; i < min(des_image.rows - 1, (int)matches.size()); i++)
// THIS LOOP IS SENSITIVE TO SEGFAULTS
{
if ((matches[i][0].distance <
thresholdMatchingNN * (matches[i][1].distance)) &&
((int)matches[i].size() <= 2 && (int)matches[i].size() > 0)) {
good_matches.push_back(matches[i][0]);
}
}
// if (good_matches.size()<1)
// good_matches.resize(0,cv::DMatch);
// Draw only "good" matches
drawMatches(object, kpObject, image, kp_image, good_matches, img_matches,
Scalar::all(-1), Scalar::all(-1), vector<char>(),
DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
if (good_matches.size() >= thresholdGoodMatches) {
// Display that the object is found
putText(img_matches, "Object Found", cvPoint(10, 50),
FONT_HERSHEY_COMPLEX_SMALL, 2, cvScalar(0, 0, 250), 1, CV_AA);
for (unsigned int i = 0; i < good_matches.size(); i++) {
// Get the keypoints from the good matches
obj.push_back(kpObject[good_matches[i].queryIdx].pt);
scene.push_back(kp_image[good_matches[i].trainIdx].pt);
}
H = findHomography(obj, scene, CV_RANSAC);
perspectiveTransform(obj_corners, scene_corners, H);
// Draw lines between the corners (the mapped object in the scene
// image )
line(img_matches, scene_corners[0] + Point2f(object.cols, 0),
scene_corners[1] + Point2f(object.cols, 0), Scalar(0, 255, 0), 4);
line(img_matches, scene_corners[1] + Point2f(object.cols, 0),
scene_corners[2] + Point2f(object.cols, 0), Scalar(0, 255, 0), 4);
line(img_matches, scene_corners[2] + Point2f(object.cols, 0),
scene_corners[3] + Point2f(object.cols, 0), Scalar(0, 255, 0), 4);
line(img_matches, scene_corners[3] + Point2f(object.cols, 0),
scene_corners[0] + Point2f(object.cols, 0), Scalar(0, 255, 0), 4);
} else {
putText(img_matches, "", cvPoint(10, 50), FONT_HERSHEY_COMPLEX_SMALL, 3,
cvScalar(0, 0, 250), 1, CV_AA);
}
// Show detected matches
imshow("Good Matches", img_matches);
escapeKey = cvWaitKey(10);
// imwrite("C:/School/Image Processing/bookIP3.jpg", img_matches);
if (frameCount > 10) escapeKey = 'q';
}
// average frames per second
if (true) {
t = ((double)getTickCount() - t) / getTickFrequency();
cout << t << " " << frameCount / t << endl;
cvWaitKey(0);
}
frameCount = 0;
escapeKey = 'a';
}
// Release camera and exit
cap.release();