c++ - Bad pointers by blurring Mat from std::vector<int>: cv::Exception -

i new opencv , have experimented several hours without success hope can give me advice. trying detect circle centers in images described here: https://solarianprogrammer.com/2015/05/08/detect-red-circles-image-using-opencv/

i using c++ in visual studio 10 on windows xp , opencv 2.2.0.

my images come in std::shared_ptr<cimg<double>> format showing black dots on white background. convert them std::vector<int> vecimagepx of length 65536 (256 rows/columns) data values between 0 , 255. have verified ok.

next, convert vector mat, done correctly. know looking @ jpg-file, pointers datastart , dataend , data not shown bad pointers according visual studio 2010 seem have valid adresses. also, mat not empty:

//[...] #include <opencv2\opencv.hpp> #include <opencv2\highgui\highgui.hpp> #include <opencv2\core\core.hpp> //[...] using namespace cv; [...]  mat tmpimage= mat(vecimagepx, false).reshape(1, 256); imwrite( "image_0.jpg", tmpimage ); // works fine bool emptyimg=tmpimage.empty(); // returns "false" 

as soon, apply filter or threshold, errors:

medianblur(tmpimage, tmpimage, 3); // give error threshold(tmpimage, tmpimage, 128, 255, thresh_binary); // give error 

error message: unhandled exception @ 0x7c812fd3 in modulatedimaging.exe: microsoft c++ exception: cv::exception @ memory location 0x0011bc14.. additionally, pointers data, dataend etc. 0.0000 <bad ptr.> according visual studio.

however, creating mat random values, using same methods, works pretty fine. nevertheless, assigning tmpimage r2 gives same error described above:

mat r2 = mat(256, 256, cv_8uc1); randu(r2, scalar::all(0), scalar::all(255)); medianblur(r2, r2, 3); // works fine threshold(r2, r2, 128, 255, thresh_binary); // works fine  mat tmpimage= mat(vecimagepx, false).reshape(1, 256); // works fine imwrite( "image_0.jpg", tmpimage ); // works fine r2=tmpimage; // works fine medianblur(r2, r2, 3); // gives error threshold(r2, r2, 128, 255, thresh_binary); // gives error 

i have e.g. tried following conversion std::vector<int> mat, there jpg.-image results in wrong stripes , filters not work well:

cv::mat tmpimage(256,256,cv_8uc1,&vecimagepx.front()); // results in wrong stripes 

what can avoid error messages?

in meantime, found solution: data type of mat tmpimage not correct using described filters! using int type=tmpimage.type(); , table below found out type of tmpimage mat cv_8uc3. however, type of r2 cv_8u1.

converting data type of tmpimage cv_8u1 using tmpimage.convertto(tmpimage,cv_8uc1); solved problems!

this table used assign type integer data type:

*+--------+----+----+----+----+------+------+------+------+ |        | c1 | c2 | c3 | c4 | c(5) | c(6) | c(7) | c(8) | +--------+----+----+----+----+------+------+------+------+ | cv_8u  |  0 |  8 | 16 | 24 |   32 |   40 |   48 |   56 | | cv_8s  |  1 |  9 | 17 | 25 |   33 |   41 |   49 |   57 | | cv_16u |  2 | 10 | 18 | 26 |   34 |   42 |   50 |   58 | | cv_16s |  3 | 11 | 19 | 27 |   35 |   43 |   51 |   59 | | cv_32s |  4 | 12 | 20 | 28 |   36 |   44 |   52 |   60 | | cv_32f |  5 | 13 | 21 | 29 |   37 |   45 |   53 |   61 | | cv_64f |  6 | 14 | 22 | 30 |   38 |   46 |   54 |   62 | +--------+----+----+----+----+------+------+------+------+