Esempio n. 1
0
void clustering(string filename) {
	Mat image = imread(filename);

	Preprocessor* pr = new Preprocessor(image);
    pr->preprocess(10);

    Mat cover;

    if(!pr->warpObject()) {
    	cout << "#WARP-UNSUCCESSFUL" << endl;
    	cover = image.clone();
    	image.release();
    	Size newSize = (cover.size().width > cover.size().height) ? Size(1024, 768) : Size(768, 1024);
    	resize(cover, cover, newSize);
    	cout << "using the whole image..." << endl;
    } else {
    	cover = pr->WarpedCover();
    	string nf = prependStringToFileName("to_swt_", filename);
    	imwrite(nf, cover);
    	cout << "#BEGIN-TO-SWT" << endl;
    	cout << nf << endl;
    	cout << "#END-TO-SWT" << endl;
    }

	cout << "#BEGIN-CLUSTERVECTOR" << endl;
	cout << Preprocessor::calculateLAB(40, cover) << endl;
	cout << "#END-CLUSTERVECTOR" << endl;
}
Esempio n. 2
0
void recognizing(string filename, vector<uint> ids) {

	Mat image = imread(filename);

	Recognizer* rcg = new Recognizer(0.70f, 0.065f);
	Preprocessor* pr = new Preprocessor(image);
    pr->preprocess(10);

    Mat cover;

    if(!pr->warpObject()) {
    	cout << "#WARP-UNSUCCESSFUL" << endl;
    	cover = image.clone();
    	image.release();
    	Size newSize = (cover.size().width > cover.size().height) ? Size(1024, 768) : Size(768, 1024);
    	resize(cover, cover, newSize);
    	cout << "using the whole image..." << endl;
    } else {
    	cover = pr->WarpedCover();
    }

    Mat trainingImage;

    for(size_t i = 0; i < ids.size(); ++i) {
    	cout << "training " << i << endl;
    	rcg->train(ids.at(i));
	}

	if(rcg->recognize(Preprocessor::kuwaharaNagaoFilter(cover)))
	{
   		Book result = rcg->LastResult();
        cout << "#BEGIN-RESULT " << result.Id() << " #END-RESULT";
    } else {
    	cout << "#BEGIN-RESULT null #END-RESULT";
    }
    cout << endl;
}