diff options
Diffstat (limited to 'thirdparty1/linux/include/opencv2/face')
| -rw-r--r-- | thirdparty1/linux/include/opencv2/face/bif.hpp | 83 | ||||
| -rw-r--r-- | thirdparty1/linux/include/opencv2/face/facerec.hpp | 166 | ||||
| -rw-r--r-- | thirdparty1/linux/include/opencv2/face/predict_collector.hpp | 127 |
3 files changed, 376 insertions, 0 deletions
diff --git a/thirdparty1/linux/include/opencv2/face/bif.hpp b/thirdparty1/linux/include/opencv2/face/bif.hpp new file mode 100644 index 0000000..c22c28c --- /dev/null +++ b/thirdparty1/linux/include/opencv2/face/bif.hpp @@ -0,0 +1,83 @@ +/* +By downloading, copying, installing or using the software you agree to this license. +If you do not agree to this license, do not download, install, +copy or use the software. + + + License Agreement + For Open Source Computer Vision Library + (3-clause BSD License) + +Copyright (C) 2000-2015, Intel Corporation, all rights reserved. +Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +Copyright (C) 2009-2015, NVIDIA Corporation, all rights reserved. +Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved. +Copyright (C) 2015, OpenCV Foundation, all rights reserved. +Copyright (C) 2015, Itseez Inc., all rights reserved. +Third party copyrights are property of their respective owners. + +Redistribution and use in source and binary forms, with or without modification, +are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + + * Neither the names of the copyright holders nor the names of the contributors + may be used to endorse or promote products derived from this software + without specific prior written permission. + +This software is provided by the copyright holders and contributors "as is" and +any express or implied warranties, including, but not limited to, the implied +warranties of merchantability and fitness for a particular purpose are disclaimed. +In no event shall copyright holders or contributors be liable for any direct, +indirect, incidental, special, exemplary, or consequential damages +(including, but not limited to, procurement of substitute goods or services; +loss of use, data, or profits; or business interruption) however caused +and on any theory of liability, whether in contract, strict liability, +or tort (including negligence or otherwise) arising in any way out of +the use of this software, even if advised of the possibility of such damage. +*/ + +#ifndef __OPENCV_BIF_HPP__ +#define __OPENCV_BIF_HPP__ + +#include "opencv2/core.hpp" + +namespace cv { +namespace face { + +/** Implementation of bio-inspired features (BIF) from the paper: + * Guo, Guodong, et al. "Human age estimation using bio-inspired features." + * Computer Vision and Pattern Recognition, 2009. CVPR 2009. + */ +class CV_EXPORTS_W BIF : public Algorithm { +public: + /** @returns The number of filter bands used for computing BIF. */ + CV_WRAP virtual int getNumBands() const = 0; + + /** @returns The number of image rotations. */ + CV_WRAP virtual int getNumRotations() const = 0; + + /** Computes features sby input image. + * @param image Input image (CV_32FC1). + * @param features Feature vector (CV_32FC1). + */ + CV_WRAP virtual void compute(InputArray image, + OutputArray features) const = 0; +}; + +/** + * @param num_bands The number of filter bands (<=8) used for computing BIF. + * @param num_rotations The number of image rotations for computing BIF. + * @returns Object for computing BIF. + */ +CV_EXPORTS_W cv::Ptr<BIF> createBIF(int num_bands = 8, int num_rotations = 12); + +} // namespace cv +} // namespace face + +#endif // #ifndef __OPENCV_FACEREC_HPP__ diff --git a/thirdparty1/linux/include/opencv2/face/facerec.hpp b/thirdparty1/linux/include/opencv2/face/facerec.hpp new file mode 100644 index 0000000..40f62f1 --- /dev/null +++ b/thirdparty1/linux/include/opencv2/face/facerec.hpp @@ -0,0 +1,166 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +// Copyright (c) 2011,2012. Philipp Wagner <bytefish[at]gmx[dot]de>. +// Third party copyrights are property of their respective owners. + +#ifndef __OPENCV_FACEREC_HPP__ +#define __OPENCV_FACEREC_HPP__ + +#include "opencv2/face.hpp" +#include "opencv2/core.hpp" + +namespace cv { namespace face { + +//! @addtogroup face +//! @{ + +// base for two classes +class CV_EXPORTS_W BasicFaceRecognizer : public FaceRecognizer +{ +public: + /** @see setNumComponents */ + CV_WRAP virtual int getNumComponents() const = 0; + /** @copybrief getNumComponents @see getNumComponents */ + CV_WRAP virtual void setNumComponents(int val) = 0; + /** @see setThreshold */ + CV_WRAP virtual double getThreshold() const = 0; + /** @copybrief getThreshold @see getThreshold */ + CV_WRAP virtual void setThreshold(double val) = 0; + CV_WRAP virtual std::vector<cv::Mat> getProjections() const = 0; + CV_WRAP virtual cv::Mat getLabels() const = 0; + CV_WRAP virtual cv::Mat getEigenValues() const = 0; + CV_WRAP virtual cv::Mat getEigenVectors() const = 0; + CV_WRAP virtual cv::Mat getMean() const = 0; +}; + +/** +@param num_components The number of components (read: Eigenfaces) kept for this Principal +Component Analysis. As a hint: There's no rule how many components (read: Eigenfaces) should be +kept for good reconstruction capabilities. It is based on your input data, so experiment with the +number. Keeping 80 components should almost always be sufficient. +@param threshold The threshold applied in the prediction. + +### Notes: + +- Training and prediction must be done on grayscale images, use cvtColor to convert between the + color spaces. +- **THE EIGENFACES METHOD MAKES THE ASSUMPTION, THAT THE TRAINING AND TEST IMAGES ARE OF EQUAL + SIZE.** (caps-lock, because I got so many mails asking for this). You have to make sure your + input data has the correct shape, else a meaningful exception is thrown. Use resize to resize + the images. +- This model does not support updating. + +### Model internal data: + +- num_components see createEigenFaceRecognizer. +- threshold see createEigenFaceRecognizer. +- eigenvalues The eigenvalues for this Principal Component Analysis (ordered descending). +- eigenvectors The eigenvectors for this Principal Component Analysis (ordered by their + eigenvalue). +- mean The sample mean calculated from the training data. +- projections The projections of the training data. +- labels The threshold applied in the prediction. If the distance to the nearest neighbor is + larger than the threshold, this method returns -1. + */ +CV_EXPORTS_W Ptr<BasicFaceRecognizer> createEigenFaceRecognizer(int num_components = 0, double threshold = DBL_MAX); + +/** +@param num_components The number of components (read: Fisherfaces) kept for this Linear +Discriminant Analysis with the Fisherfaces criterion. It's useful to keep all components, that +means the number of your classes c (read: subjects, persons you want to recognize). If you leave +this at the default (0) or set it to a value less-equal 0 or greater (c-1), it will be set to the +correct number (c-1) automatically. +@param threshold The threshold applied in the prediction. If the distance to the nearest neighbor +is larger than the threshold, this method returns -1. + +### Notes: + +- Training and prediction must be done on grayscale images, use cvtColor to convert between the + color spaces. +- **THE FISHERFACES METHOD MAKES THE ASSUMPTION, THAT THE TRAINING AND TEST IMAGES ARE OF EQUAL + SIZE.** (caps-lock, because I got so many mails asking for this). You have to make sure your + input data has the correct shape, else a meaningful exception is thrown. Use resize to resize + the images. +- This model does not support updating. + +### Model internal data: + +- num_components see createFisherFaceRecognizer. +- threshold see createFisherFaceRecognizer. +- eigenvalues The eigenvalues for this Linear Discriminant Analysis (ordered descending). +- eigenvectors The eigenvectors for this Linear Discriminant Analysis (ordered by their + eigenvalue). +- mean The sample mean calculated from the training data. +- projections The projections of the training data. +- labels The labels corresponding to the projections. + */ +CV_EXPORTS_W Ptr<BasicFaceRecognizer> createFisherFaceRecognizer(int num_components = 0, double threshold = DBL_MAX); + +class CV_EXPORTS_W LBPHFaceRecognizer : public FaceRecognizer +{ +public: + /** @see setGridX */ + CV_WRAP virtual int getGridX() const = 0; + /** @copybrief getGridX @see getGridX */ + CV_WRAP virtual void setGridX(int val) = 0; + /** @see setGridY */ + CV_WRAP virtual int getGridY() const = 0; + /** @copybrief getGridY @see getGridY */ + CV_WRAP virtual void setGridY(int val) = 0; + /** @see setRadius */ + CV_WRAP virtual int getRadius() const = 0; + /** @copybrief getRadius @see getRadius */ + CV_WRAP virtual void setRadius(int val) = 0; + /** @see setNeighbors */ + CV_WRAP virtual int getNeighbors() const = 0; + /** @copybrief getNeighbors @see getNeighbors */ + CV_WRAP virtual void setNeighbors(int val) = 0; + /** @see setThreshold */ + CV_WRAP virtual double getThreshold() const = 0; + /** @copybrief getThreshold @see getThreshold */ + CV_WRAP virtual void setThreshold(double val) = 0; + CV_WRAP virtual std::vector<cv::Mat> getHistograms() const = 0; + CV_WRAP virtual cv::Mat getLabels() const = 0; +}; + +/** +@param radius The radius used for building the Circular Local Binary Pattern. The greater the +radius, the +@param neighbors The number of sample points to build a Circular Local Binary Pattern from. An +appropriate value is to use `8` sample points. Keep in mind: the more sample points you include, +the higher the computational cost. +@param grid_x The number of cells in the horizontal direction, 8 is a common value used in +publications. The more cells, the finer the grid, the higher the dimensionality of the resulting +feature vector. +@param grid_y The number of cells in the vertical direction, 8 is a common value used in +publications. The more cells, the finer the grid, the higher the dimensionality of the resulting +feature vector. +@param threshold The threshold applied in the prediction. If the distance to the nearest neighbor +is larger than the threshold, this method returns -1. + +### Notes: + +- The Circular Local Binary Patterns (used in training and prediction) expect the data given as + grayscale images, use cvtColor to convert between the color spaces. +- This model supports updating. + +### Model internal data: + +- radius see createLBPHFaceRecognizer. +- neighbors see createLBPHFaceRecognizer. +- grid_x see createLBPHFaceRecognizer. +- grid_y see createLBPHFaceRecognizer. +- threshold see createLBPHFaceRecognizer. +- histograms Local Binary Patterns Histograms calculated from the given training data (empty if + none was given). +- labels Labels corresponding to the calculated Local Binary Patterns Histograms. + */ +CV_EXPORTS_W Ptr<LBPHFaceRecognizer> createLBPHFaceRecognizer(int radius=1, int neighbors=8, int grid_x=8, int grid_y=8, double threshold = DBL_MAX); + +//! @} + +}} //namespace cv::face + +#endif //__OPENCV_FACEREC_HPP__ diff --git a/thirdparty1/linux/include/opencv2/face/predict_collector.hpp b/thirdparty1/linux/include/opencv2/face/predict_collector.hpp new file mode 100644 index 0000000..a9f907d --- /dev/null +++ b/thirdparty1/linux/include/opencv2/face/predict_collector.hpp @@ -0,0 +1,127 @@ +/* +By downloading, copying, installing or using the software you agree to this license. +If you do not agree to this license, do not download, install, +copy or use the software. + + + License Agreement + For Open Source Computer Vision Library + (3-clause BSD License) + +Copyright (C) 2000-2015, Intel Corporation, all rights reserved. +Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +Copyright (C) 2009-2015, NVIDIA Corporation, all rights reserved. +Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved. +Copyright (C) 2015, OpenCV Foundation, all rights reserved. +Copyright (C) 2015, Itseez Inc., all rights reserved. +Third party copyrights are property of their respective owners. + +Redistribution and use in source and binary forms, with or without modification, +are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + + * Neither the names of the copyright holders nor the names of the contributors + may be used to endorse or promote products derived from this software + without specific prior written permission. + +This software is provided by the copyright holders and contributors "as is" and +any express or implied warranties, including, but not limited to, the implied +warranties of merchantability and fitness for a particular purpose are disclaimed. +In no event shall copyright holders or contributors be liable for any direct, +indirect, incidental, special, exemplary, or consequential damages +(including, but not limited to, procurement of substitute goods or services; +loss of use, data, or profits; or business interruption) however caused +and on any theory of liability, whether in contract, strict liability, +or tort (including negligence or otherwise) arising in any way out of +the use of this software, even if advised of the possibility of such damage. +*/ + +#ifndef __OPENCV_PREDICT_COLLECTOR_HPP__ +#define __OPENCV_PREDICT_COLLECTOR_HPP__ + +#include <vector> +#include <map> +#include <utility> +#include <cfloat> + +#include "opencv2/core/cvstd.hpp" + +namespace cv { +namespace face { +//! @addtogroup face +//! @{ +/** @brief Abstract base class for all strategies of prediction result handling +*/ +class CV_EXPORTS_W PredictCollector +{ +public: + virtual ~PredictCollector() {} + + /** @brief Interface method called by face recognizer before results processing + @param size total size of prediction evaluation that recognizer could perform + */ + virtual void init(size_t size) { (void)size; } + + /** @brief Interface method called by face recognizer for each result + @param label current prediction label + @param dist current prediction distance (confidence) + */ + virtual bool collect(int label, double dist) = 0; +}; + +/** @brief Default predict collector + +Trace minimal distance with treshhold checking (that is default behavior for most predict logic) +*/ +class CV_EXPORTS_W StandardCollector : public PredictCollector +{ +public: + struct PredictResult + { + int label; + double distance; + PredictResult(int label_ = -1, double distance_ = DBL_MAX) : label(label_), distance(distance_) {} + }; +protected: + double threshold; + PredictResult minRes; + std::vector<PredictResult> data; +public: + /** @brief Constructor + @param threshold_ set threshold + */ + StandardCollector(double threshold_ = DBL_MAX); + /** @brief overloaded interface method */ + void init(size_t size); + /** @brief overloaded interface method */ + bool collect(int label, double dist); + /** @brief Returns label with minimal distance */ + CV_WRAP int getMinLabel() const; + /** @brief Returns minimal distance value */ + CV_WRAP double getMinDist() const; + /** @brief Return results as vector + @param sorted If set, results will be sorted by distance + Each values is a pair of label and distance. + */ + CV_WRAP std::vector< std::pair<int, double> > getResults(bool sorted = false) const; + /** @brief Return results as map + Labels are keys, values are minimal distances + */ + std::map<int, double> getResultsMap() const; + /** @brief Static constructor + @param threshold set threshold + */ + CV_WRAP static Ptr<StandardCollector> create(double threshold = DBL_MAX); +}; + +//! @} +} +} + +#endif |