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162 lines
5.6 KiB
162 lines
5.6 KiB
/* |
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By downloading, copying, installing or using the software you agree to this |
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license. 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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License Agreement |
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For Open Source Computer Vision Library |
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(3-clause BSD License) |
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Copyright (C) 2013, OpenCV Foundation, all rights reserved. |
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Third party copyrights are property of their respective owners. |
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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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* Redistributions 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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* Redistributions 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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* Neither the names of the copyright holders nor the names of the contributors |
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may be used to endorse or promote products derived from this software |
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without specific prior written permission. |
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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 |
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disclaimed. In no event shall copyright holders or contributors be liable for |
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any direct, 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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This file was part of GSoC Project: Facemark API for OpenCV |
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Final report: https://gist.github.com/kurnianggoro/74de9121e122ad0bd825176751d47ecc |
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Student: Laksono Kurnianggoro |
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Mentor: Delia Passalacqua |
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*/ |
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#ifndef __OPENCV_FACEMARK_AAM_HPP__ |
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#define __OPENCV_FACEMARK_AAM_HPP__ |
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#include "opencv2/face/facemark_train.hpp" |
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namespace cv { |
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namespace face { |
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//! @addtogroup face |
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//! @{ |
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class CV_EXPORTS_W FacemarkAAM : public FacemarkTrain |
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{ |
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public: |
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struct CV_EXPORTS Params |
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{ |
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/** |
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* \brief Constructor |
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*/ |
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Params(); |
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/** |
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* \brief Read parameters from file, currently unused |
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*/ |
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void read(const FileNode& /*fn*/); |
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/** |
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* \brief Read parameters from file, currently unused |
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*/ |
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void write(FileStorage& /*fs*/) const; |
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std::string model_filename; |
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int m; |
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int n; |
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int n_iter; |
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bool verbose; |
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bool save_model; |
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int max_m, max_n, texture_max_m; |
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std::vector<float>scales; |
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}; |
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/** |
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* \brief Optional parameter for fitting process. |
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*/ |
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struct CV_EXPORTS Config |
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{ |
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Config( Mat rot = Mat::eye(2,2,CV_32F), |
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Point2f trans = Point2f(0.0f, 0.0f), |
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float scaling = 1.0f, |
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int scale_id=0 |
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); |
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Mat R; |
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Point2f t; |
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float scale; |
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int model_scale_idx; |
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}; |
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/** |
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* \brief Data container for the facemark::getData function |
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*/ |
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struct CV_EXPORTS Data |
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{ |
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std::vector<Point2f> s0; |
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}; |
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/** |
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* \brief The model of AAM Algorithm |
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*/ |
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struct CV_EXPORTS Model |
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{ |
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std::vector<float>scales; |
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//!< defines the scales considered to build the model |
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/*warping*/ |
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std::vector<Vec3i> triangles; |
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//!< each element contains 3 values, represent index of facemarks that construct one triangle (obtained using delaunay triangulation) |
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struct Texture{ |
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int max_m; //!< unused delete |
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Rect resolution; |
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//!< resolution of the current scale |
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Mat A; |
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//!< gray values from all face region in the dataset, projected in PCA space |
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Mat A0; |
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//!< average of gray values from all face region in the dataset |
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Mat AA; |
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//!< gray values from all erorded face region in the dataset, projected in PCA space |
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Mat AA0; |
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//!< average of gray values from all erorded face region in the dataset |
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std::vector<std::vector<Point> > textureIdx; |
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//!< index for warping of each delaunay triangle region constructed by 3 facemarks |
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std::vector<Point2f> base_shape; |
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//!< basic shape, normalized to be fit in an image with current detection resolution |
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std::vector<int> ind1; |
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//!< index of pixels for mapping process to obtains the grays values of face region |
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std::vector<int> ind2; |
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//!< index of pixels for mapping process to obtains the grays values of eroded face region |
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}; |
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std::vector<Texture> textures; |
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//!< a container to holds the texture data for each scale of fitting |
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/*shape*/ |
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std::vector<Point2f> s0; |
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//!< the basic shape obtained from training dataset |
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Mat S,Q; |
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//!< the encoded shapes from training data |
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}; |
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//! overload with additional Config structures |
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virtual bool fitConfig( InputArray image, InputArray roi, OutputArrayOfArrays _landmarks, const std::vector<Config> &runtime_params ) = 0; |
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//! initializer |
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static Ptr<FacemarkAAM> create(const FacemarkAAM::Params ¶meters = FacemarkAAM::Params() ); |
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virtual ~FacemarkAAM() {} |
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}; /* AAM */ |
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//! @} |
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} /* namespace face */ |
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} /* namespace cv */ |
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#endif
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