Debugging 退出显示图像OpenCV时堆损坏
我正在做一些基于本教程的算术运算 它单独工作得很好,但当我将其放入函数并从主函数调用它时,会出现堆损坏。程序显示图像,然后当我按空格键关闭程序时,它会中断Debugging 退出显示图像OpenCV时堆损坏,debugging,opencv,Debugging,Opencv,我正在做一些基于本教程的算术运算 它单独工作得很好,但当我将其放入函数并从主函数调用它时,会出现堆损坏。程序显示图像,然后当我按空格键关闭程序时,它会中断 int main(int argc, char ** argv) { // Part 2 panorama Mat im1=imread("panorama_image1.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat im2=imread("panorama_image2.jpg", CV
int main(int argc, char ** argv)
{
// Part 2 panorama
Mat im1=imread("panorama_image1.jpg", CV_LOAD_IMAGE_GRAYSCALE);
Mat im2=imread("panorama_image2.jpg", CV_LOAD_IMAGE_GRAYSCALE);
immosaic(im1,im2);
return 0;
}
这是马赛克函数,复制自教程
void immosaic(Mat im_object, Mat im_scene)
{
//-- Step 1: Detect the keypoints using SURF Detector
int minHessian = 400;
SurfFeatureDetector detector( minHessian );
std::vector<KeyPoint> keypoints_object, keypoints_scene;
detector.detect( im_object, keypoints_object );
detector.detect( im_scene, keypoints_scene );
//-- Step 2: Calculate descriptors (feature vectors)
SurfDescriptorExtractor extractor;
Mat descriptors_object, descriptors_scene;
extractor.compute( im_object, keypoints_object, descriptors_object );
extractor.compute( im_scene, keypoints_scene, descriptors_scene );
//-- Step 3: Matching descriptor vectors using FLANN matcher
FlannBasedMatcher matcher;
std::vector< DMatch > matches;
matcher.match( descriptors_object, descriptors_scene, matches );
double max_dist = 0; double min_dist = 100;
//-- Quick calculation of max and min distances between keypoints
for( int i = 0; i < descriptors_object.rows; i++ )
{
double dist = matches[i].distance;
if( dist < min_dist ) min_dist = dist;
if( dist > max_dist ) max_dist = dist;
}
//-- Draw only "good" matches (i.e. whose distance is less than 3*min_dist )
std::vector< DMatch > good_matches;
for( int i = 0; i < descriptors_object.rows; i++ )
{
if( matches[i].distance < 3*min_dist )
good_matches.push_back( matches[i]);
}
Mat img_matches;
drawMatches( im_object, keypoints_object, im_scene, keypoints_scene,
good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
//-- Localize the object
std::vector<Point2f> obj;
std::vector<Point2f> scene;
for( int i = 0; i < good_matches.size(); i++ )
{
//-- Get the keypoints from the good matches
obj.push_back( keypoints_object[ good_matches[i].queryIdx ].pt );
scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt );
}
Mat H = findHomography( obj, scene, CV_RANSAC );
//-- Get the corners from the image_1 ( the object to be "detected" )
std::vector<Point2f> obj_corners(4);
obj_corners[0] = cvPoint(0,0); obj_corners[1] = cvPoint( im_object.cols, 0 );
obj_corners[2] = cvPoint( im_object.cols, im_object.rows ); obj_corners[3] = cvPoint( 0, im_object.rows );
std::vector<Point2f> scene_corners(4);
perspectiveTransform( obj_corners, scene_corners, H);
//-- Draw lines between the corners (the mapped object in the scene - image_2 )
line( img_matches, scene_corners[0] + Point2f( im_object.cols, 0), scene_corners[1] + Point2f( im_object.cols, 0), Scalar(0, 255, 0), 4 );
line( img_matches, scene_corners[1] + Point2f( im_object.cols, 0), scene_corners[2] + Point2f( im_object.cols, 0), Scalar( 0, 255, 0), 4 );
line( img_matches, scene_corners[2] + Point2f( im_object.cols, 0), scene_corners[3] + Point2f( im_object.cols, 0), Scalar( 0, 255, 0), 4 );
line( img_matches, scene_corners[3] + Point2f( im_object.cols, 0), scene_corners[0] + Point2f( im_object.cols, 0), Scalar( 0, 255, 0), 4 );
//-- Show detected matches
namedWindow("Matching");
imshow( "Matching", img_matches );
waitKey(0);
//return 0;
}
void immosaic(Mat im_对象,Mat im_场景)
{
//--步骤1:使用SURF检测器检测关键点
int minHessian=400;
表面特征检测器(minHessian);
std::矢量关键点\对象,关键点\场景;
检测器。检测(im\u对象、关键点\u对象);
检测器。检测(im_场景、关键点_场景);
//--步骤2:计算描述符(特征向量)
表面描述符牵引器;
Mat描述符\u对象,描述符\u场景;
compute(im\u对象、keypoints\u对象、描述符\u对象);
计算(im场景、关键点场景、描述符场景);
//--步骤3:使用FLANN匹配器匹配描述符向量
法兰巴斯德匹配器;
标准::向量匹配;
匹配(描述符\对象、描述符\场景、匹配);
双最大距离=0;双最小距离=100;
//--快速计算关键点之间的最大和最小距离
对于(int i=0;i最大距离)最大距离=距离;
}
//--仅绘制“良好”匹配(即距离小于3*min\u dist)
标准::矢量良好匹配;
对于(int i=0;i
我也遇到了这个问题。我的问题是我运行的是Visual Studio 2012,但使用的是为Visual Studio 2010构建的openCV(2.4.3)中的lib文件
如果这是你的情况,你有两个选择
我尝试了同样的教程,遇到了同样的问题,并在网上尝试了所有的方法,但没有成功。刚才我终于修好了。导致损坏的不是退出显示,而是从函数返回。换句话说,在这些DLL中块结束后,清理过程中存在一些问题 在我的例子中,问题是混合加载调试dll和发布dll 通过仔细查看这些加载信息,您可以看到是否存在相同的问题。要解决这个问题,请将属性->链接器->输入->附加依赖项更改为仅调试或发布。 打扫干净,重新建造。幸运的话,你不会再看到这个问题了 希望能有帮助