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Open Source Computer Vision Library
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143 lines
3.9 KiB
143 lines
3.9 KiB
Soft Cascade Training |
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======================= |
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.. highlight:: cpp |
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Soft Cascade Detector Training |
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-------------------------------------------- |
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softcascade::Octave |
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------------------- |
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.. ocv:class:: softcascade::Octave : public Algorithm |
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Public interface for soft cascade training algorithm. :: |
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class Octave : public Algorithm |
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{ |
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public: |
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enum { |
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// Direct backward pruning. (Cha Zhang and Paul Viola) |
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DBP = 1, |
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// Multiple instance pruning. (Cha Zhang and Paul Viola) |
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MIP = 2, |
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// Originally proposed by L. Bourdev and J. Brandt |
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HEURISTIC = 4 }; |
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virtual ~Octave(); |
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static cv::Ptr<Octave> create(cv::Rect boundingBox, int npositives, int nnegatives, int logScale, int shrinkage); |
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virtual bool train(const Dataset* dataset, const FeaturePool* pool, int weaks, int treeDepth) = 0; |
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virtual void setRejectThresholds(OutputArray thresholds) = 0; |
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virtual void write( cv::FileStorage &fs, const FeaturePool* pool, InputArray thresholds) const = 0; |
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virtual void write( CvFileStorage* fs, String name) const = 0; |
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}; |
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softcascade::Octave::~Octave |
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--------------------------------------- |
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Destructor for Octave. |
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.. ocv:function:: softcascade::Octave::~Octave() |
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softcascade::Octave::train |
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-------------------------- |
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.. ocv:function:: bool softcascade::Octave::train(const Dataset* dataset, const FeaturePool* pool, int weaks, int treeDepth) |
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:param dataset an object that allows communicate for training set. |
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:param pool an object that presents feature pool. |
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:param weaks a number of weak trees should be trained. |
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:param treeDepth a depth of resulting weak trees. |
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softcascade::Octave::setRejectThresholds |
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---------------------------------------- |
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.. ocv:function:: void softcascade::Octave::setRejectThresholds(OutputArray thresholds) |
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:param thresholds an output array of resulted rejection vector. Have same size as number of trained stages. |
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softcascade::Octave::write |
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-------------------------- |
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.. ocv:function:: void softcascade::Octave::train(cv::FileStorage &fs, const FeaturePool* pool, InputArray thresholds) const |
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.. ocv:function:: void softcascade::Octave::train( CvFileStorage* fs, String name) const |
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:param fs an output file storage to store trained detector. |
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:param pool an object that presents feature pool. |
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:param dataset a rejection vector that should be included in detector xml file. |
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:param name a name of root node for trained detector. |
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softcascade::FeaturePool |
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------------------------ |
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.. ocv:class:: softcascade::FeaturePool |
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Public interface for feature pool. This is a hight level abstraction for training random feature pool. :: |
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class FeaturePool |
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{ |
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public: |
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virtual int size() const = 0; |
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virtual float apply(int fi, int si, const Mat& channels) const = 0; |
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virtual void write( cv::FileStorage& fs, int index) const = 0; |
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virtual ~FeaturePool(); |
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}; |
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softcascade::FeaturePool::size |
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------------------------------ |
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Returns size of feature pool. |
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.. ocv:function:: int softcascade::FeaturePool::size() const |
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softcascade::FeaturePool::~FeaturePool |
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-------------------------------------- |
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FeaturePool destructor. |
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.. ocv:function:: softcascade::FeaturePool::~FeaturePool() |
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softcascade::FeaturePool::write |
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------------------------------- |
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Write specified feature from feature pool to file storage. |
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.. ocv:function:: void softcascade::FeaturePool::write( cv::FileStorage& fs, int index) const |
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:param fs an output file storage to store feature. |
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:param index an index of feature that should be stored. |
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softcascade::FeaturePool::apply |
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------------------------------- |
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Compute feature on integral channel image. |
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.. ocv:function:: float softcascade::FeaturePool::apply(int fi, int si, const Mat& channels) const |
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:param fi an index of feature that should be computed. |
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:param si an index of sample. |
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:param fs a channel matrix. |