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Adding stubb of documentation for the Dynamic feature detectors
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@ -308,6 +308,47 @@ protected:
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};
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\end{lstlisting}
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\cvclass{DynamicDetectorAdaptor}
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An adaptively adjusting detector that iteratively detects until the desired number
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of features are found.
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Adapters can easily be implemented for any detector through the creation of an Adjuster
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object.
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Beware that this is not thread safe - as the adjustment of parameters breaks the const
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of the detection routine...
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\begin{lstlisting}
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template<typename Adjuster>
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class DynamicDetectorAdaptor: public FeatureDetector {
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public:
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DynamicDetectorAdaptor(int min_features, int max_features, int max_iters,
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const Adjuster& a = Adjuster());
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...
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};
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//expected Adjuster interface
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class MyAdjuster {
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public:
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//this should call a FeatureDetector and populate keypoints
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//e.g. FASTFeatureDetector(thresh).detect(img,mask,keypoints)
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void detect(const Mat& img, const Mat& mask, std::vector<KeyPoint>& keypoints) const;
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//called if there are too few features detected, should adjust feature detector params
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//accordingly
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void tooFew(int min, int n_detected);
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//called if there are too many features detected, should adjust feature detector params
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//accordingly
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void tooMany(int max, int n_detected);
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//return whether or not the threshhold is beyond
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//a useful point
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bool good() const;
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\end{lstlisting}
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\cvCppFunc{createFeatureDetector}
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Feature detector factory that creates \cvCppCross{FeatureDetector} of given type with
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default parameters (rather using default constructor).
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