fixing issue #4969 of Itseez/opencv.
Someone forgot to wrap the load function for SVMs in the corresponding ml python module. Fixed that.
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@ -719,6 +719,10 @@ public:
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Use StatModel::train to train the model. Since %SVM has several parameters, you may want to
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Use StatModel::train to train the model. Since %SVM has several parameters, you may want to
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find the best parameters for your problem, it can be done with SVM::trainAuto. */
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find the best parameters for your problem, it can be done with SVM::trainAuto. */
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CV_WRAP static Ptr<SVM> create();
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CV_WRAP static Ptr<SVM> create();
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CV_WRAP virtual void read( const FileNode& fn ) = 0;
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CV_WRAP static Ptr<SVM> load(const String& fs);
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};
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};
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/****************************************************************************************\
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/****************************************************************************************\
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@ -2261,6 +2261,17 @@ Ptr<SVM> SVM::create()
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return makePtr<SVMImpl>();
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return makePtr<SVMImpl>();
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}
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}
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Ptr<SVM> SVM::load(const String& filename)
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{
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FileStorage fs;
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fs.open(filename, FileStorage::READ);
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Ptr<SVM> svm = makePtr<SVMImpl>();
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svm->read(fs.getFirstTopLevelNode());
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return svm;
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}
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Mat SVM::getUncompressedSupportVectors() const
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Mat SVM::getUncompressedSupportVectors() const
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{
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{
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const SVMImpl* this_ = dynamic_cast<const SVMImpl*>(this);
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const SVMImpl* this_ = dynamic_cast<const SVMImpl*>(this);
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