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@ -734,6 +734,12 @@ void LBPH::train(InputArray _src, InputArray _lbls) { |
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// get the vector of matrices
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vector<Mat> src; |
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_src.getMatVector(src); |
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for (vector<Mat>::const_iterator image = src.begin(); image != src.end(); ++image) { |
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if (image->channels() != 1) { |
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string error_message = format("The images must be single channel (grayscale), but an image has %d channels.", image->channels()); |
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CV_Error(CV_StsUnsupportedFormat, error_message); |
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} |
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} |
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// turn the label matrix into a vector
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Mat labels = _lbls.getMat(); |
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CV_Assert( labels.type() == CV_32S && (labels.cols == 1 || labels.rows == 1)); |
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@ -760,6 +766,10 @@ void LBPH::train(InputArray _src, InputArray _lbls) { |
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void LBPH::predict(InputArray _src, int &minClass, double &minDist) const { |
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Mat src = _src.getMat(); |
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if (src.channels() != 1) { |
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string error_message = format("The image must be single channel (grayscale), but the image has %d channels.", src.channels()); |
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CV_Error(CV_StsUnsupportedFormat, error_message); |
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} |
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// get the spatial histogram from input image
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Mat lbp_image = elbp(src, _radius, _neighbors); |
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Mat query = spatial_histogram( |
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