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143 lines
4.9 KiB
143 lines
4.9 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2015, Itseez Inc, all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Itseez Inc or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#ifndef __DPM_MODEL__ |
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#define __DPM_MODEL__ |
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#include "opencv2/core.hpp" |
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#include <string> |
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#include <vector> |
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namespace cv |
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{ |
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namespace dpm |
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{ |
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/** @brief This class contains DPM model parameters |
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*/ |
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class Model |
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{ |
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public: |
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// size of HOG feature cell (e.g., 8 pixels) |
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int sBin; |
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// number of levels per octave in feature pyramid |
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int interval; |
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// maximum width of the detection window |
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int maxSizeX; |
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// maximum height of the detection window |
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int maxSizeY; |
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// dimension of HOG features |
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int numFeatures; |
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// number of components in the model |
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int numComponents; |
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// number of parts per component |
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std::vector<int> numParts; |
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// size of root filters |
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std::vector< Size > rootFilterDims; |
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// size of part filters |
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std::vector< Size > partFilterDims; |
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// root filters |
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std::vector< Mat > rootFilters; |
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// part filters |
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std::vector< Mat > partFilters; |
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// global detecion threshold |
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float scoreThresh; |
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// component indexed array of part orderings |
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std::vector< std::vector<int> > partOrder; |
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// component indexed offset (a.k.a. bias) values |
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std::vector<float> bias; |
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// location/scale weight |
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std::vector< std::vector< double > > locationWeight; |
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// idea relative positions for each deformation model |
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std::vector< std::vector< double > > anchors; |
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// array of deformation models |
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std::vector< std::vector< double > > defs; |
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// map: pFind[component][part] => part filter index |
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std::vector< std::vector<int> > pFind; |
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public: |
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Model () {} |
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virtual ~Model () {} |
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// get number of part filters |
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int getNumPartFilters() |
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{ |
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return (int) partFilters.size(); |
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} |
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// get number of deformation parameters |
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int getNumDefParams() |
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{ |
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return (int) defs.size(); |
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} |
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virtual void initModel() {}; |
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virtual bool serialize(const std::string &filename) const = 0; |
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virtual bool deserialize(const std::string &filename) = 0; |
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}; |
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class CascadeModel : public Model |
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{ |
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public: |
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// PCA coefficient matrix |
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Mat pcaCoeff; |
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// number of dimensions used for the PCA projection |
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int pcaDim; |
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// component indexed arrays of pruning threshold |
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std::vector< std::vector< double > > prunThreshold; |
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// root pca filters |
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std::vector< Mat > rootPCAFilters; |
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// part PCA filters |
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std::vector< Mat > partPCAFilters; |
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public: |
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CascadeModel() {} |
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~CascadeModel() {} |
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void initModel(); |
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bool serialize(const std::string &filename) const; |
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bool deserialize(const std::string &filename); |
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}; |
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} // namespace lsvm |
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} // namespace cv |
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#endif // __DPM_MODEL_
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