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propagated 2 fixed from 2.4 to trunk
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@ -1956,7 +1956,7 @@ The function ``mulSpectrums`` performs the per-element multiplication of the two
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The function, together with
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:ocv:func:`dft` and
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:ocv:func:`idft` , may be used to calculate convolution (pass ``conj=false`` ) or correlation (pass ``conj=false`` ) of two arrays rapidly. When the arrays are complex, they are simply multiplied (per element) with an optional conjugation of the second-array elements. When the arrays are real, they are assumed to be CCS-packed (see
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:ocv:func:`idft` , may be used to calculate convolution (pass ``conj=false`` ) or correlation (pass ``conj=true`` ) of two arrays rapidly. When the arrays are complex, they are simply multiplied (per element) with an optional conjugation of the second-array elements. When the arrays are real, they are assumed to be CCS-packed (see
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:ocv:func:`dft` for details).
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@ -25,6 +25,17 @@
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using namespace cv;
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using namespace std;
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Mat toGrayscale(InputArray _src) {
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Mat src = _src.getMat();
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// only allow one channel
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if(src.channels() != 1)
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CV_Error(CV_StsBadArg, "Only Matrices with one channel are supported");
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// create and return normalized image
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Mat dst;
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cv::normalize(_src, dst, 0, 255, NORM_MINMAX, CV_8UC1);
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return dst;
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}
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void read_csv(const string& filename, vector<Mat>& images, vector<int>& labels, char separator = ';') {
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std::ifstream file(filename.c_str(), ifstream::in);
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if (!file)
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@ -79,10 +90,10 @@ int main(int argc, const char *argv[]) {
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for (int i = 0; i < min(10, W.cols); i++) {
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// get eigenvector #i
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Mat ev = W.col(i).clone();
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// reshape to original site
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Mat grayscale, cgrayscale;
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cvtColor(ev.reshape(1, height), grayscale, COLOR_BGR2GRAY);
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// reshape to original size AND normalize between [0...255]
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Mat grayscale = toGrayscale(ev.reshape(1, height));
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// show image (with Jet colormap)
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Mat cgrayscale;
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applyColorMap(grayscale, cgrayscale, COLORMAP_JET);
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imshow(format("%d", i), cgrayscale);
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}
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