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82 lines
3.1 KiB
82 lines
3.1 KiB
Objectness Algorithms |
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.. highlight:: cpp |
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Objectness is usually represented as a value which reflects how likely an image window covers an object of any category. Algorithms belonging to this category, avoid making decisions early on, by proposing a small number of category-independent proposals, that are expected to cover all objects in an image. Being able to perceive objects before identifying them is closely related to bottom up visual attention (saliency) |
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Presently, the Binarized normed gradients algorithm [BING]_ has been implemented. |
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.. [BING] Cheng, Ming-Ming, et al. "BING: Binarized normed gradients for objectness estimation at 300fps." IEEE CVPR. 2014. |
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ObjectnessBING |
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.. ocv:class:: ObjectnessBING |
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Implementation of BING from :ocv:class:`Objectness`:: |
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class CV_EXPORTS ObjectnessBING : public Objectness |
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{ |
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public: |
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ObjectnessBING(); |
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~ObjectnessBING(); |
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void read(); |
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void write() const; |
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vector<float> getobjectnessValues(); |
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void setTrainingPath( string trainingPath ); |
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void setBBResDir( string resultsDir ); |
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protected: |
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bool computeSaliencyImpl( const InputArray src, OutputArray dst ); |
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}; |
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ObjectnessBING::ObjectnessBING |
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------------------------------ |
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Constructor |
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.. ocv:function:: ObjectnessBING::ObjectnessBING() |
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ObjectnessBING::getobjectnessValues |
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----------------------------------- |
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Return the list of the rectangles' objectness value, in the same order as the *vector<Vec4i> objectnessBoundingBox* returned by the algorithm (in computeSaliencyImpl function). |
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The bigger value these scores are, it is more likely to be an object window. |
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.. ocv:function:: vector<float> ObjectnessBING::getobjectnessValues() |
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ObjectnessBING::setTrainingPath |
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-------------------------------- |
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This is a utility function that allows to set the correct path from which the algorithm will load the trained model. |
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.. ocv:function:: void ObjectnessBING::setTrainingPath( string trainingPath ) |
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:param trainingPath: trained model path |
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ObjectnessBING::setBBResDir |
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--------------------------- |
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This is a utility function that allows to set an arbitrary path in which the algorithm will save the optional results |
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(ie writing on file the total number and the list of rectangles returned by objectess, one for each row). |
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.. ocv:function:: void ObjectnessBING::setBBResDir( string resultsDir ) |
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:param setBBResDir: results' folder path |
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ObjectnessBING::computeSaliencyImpl |
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----------------------------------- |
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Performs all the operations and calls all internal functions necessary for the accomplishment of the Binarized normed gradients algorithm. |
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.. ocv:function:: bool ObjectnessBING::computeSaliencyImpl( const InputArray image, OutputArray objectnessBoundingBox ) |
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:param image: input image. According to the needs of this specialized algorithm, the param image is a single *Mat* |
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:param saliencyMap: objectness Bounding Box vector. According to the result given by this specialized algorithm, the objectnessBoundingBox is a *vector<Vec4i>*. |
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Each bounding box is represented by a *Vec4i* for (minX, minY, maxX, maxY). |
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