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both mean and sigma are actually simple Scalars, not images. in the case of your Hog features, only a single channel is used, so, -- there won't be much to see, if you concat those to another Mat.

both mean and sigma are actually simple Scalars, not images. in the case of your Hog features, only a single channel is used, so, -- there won't be much to see, if you concat those to another Mat.

cout << "mean " << mean << " sigma " << sigma << endl;

both mean and sigma are actually simple Scalars, not images. in the case of your Hog features, only a single channel is used, so, -- there won't be much to see, if you concat those to another Mat.

you could try to print them out on console, like:

cout << "mean " << mean << " sigma " << sigma << endl;

storage << "hogfeature" << HogFeature;
storage.release(); // nothing will happen, unless you actually flush/close it.

both mean and sigma are actually simple Scalars, not images. in the case of your Hog features, only a single channel is used, so, -- there won't be much to see, if you concat those to another Mat.

you could try to print them out on console, like:

cout << "mean " << mean << " sigma " << sigma << endl;

then, your filestorage idea lacks the actual writing of the Hog features, which would be:

storage << "hogfeature" << HogFeature;
HogFeat;
storage.release(); // nothing will happen, unless you actually flush/close it.

both mean and sigma are actually simple Scalars, not images. in the case of your Hog features, only a single channel is used, so, -- there won't be much to see, if you concat those to another Mat.

you could try to print them out on console, like:

cout << "mean " << mean << " sigma " << sigma << endl;

then, your filestorage idea lacks the actual writing of the Hog features, which would be:

storage << "hogfeature" << HogFeat;
HogFeat; // basically - it's a key-value store.
storage.release(); // nothing will happen, unless you actually flush/close it.