///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2017, Carnegie Mellon University and University of Cambridge,
// all rights reserved.
//
// ACADEMIC OR NON-PROFIT ORGANIZATION NONCOMMERCIAL RESEARCH USE ONLY
//
// BY USING OR DOWNLOADING THE SOFTWARE, YOU ARE AGREEING TO THE TERMS OF THIS LICENSE AGREEMENT.  
// IF YOU DO NOT AGREE WITH THESE TERMS, YOU MAY NOT USE OR DOWNLOAD THE SOFTWARE.
//
// License can be found in OpenFace-license.txt
//
//     * Any publications arising from the use of this software, including but
//       not limited to academic journal and conference publications, technical
//       reports and manuals, must cite at least one of the following works:
//
//       OpenFace: an open source facial behavior analysis toolkit
//       Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency
//       in IEEE Winter Conference on Applications of Computer Vision, 2016  
//
//       Rendering of Eyes for Eye-Shape Registration and Gaze Estimation
//       Erroll Wood, Tadas Baltrušaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling 
//       in IEEE International. Conference on Computer Vision (ICCV),  2015 
//
//       Cross-dataset learning and person-speci?c normalisation for automatic Action Unit detection
//       Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson 
//       in Facial Expression Recognition and Analysis Challenge, 
//       IEEE International Conference on Automatic Face and Gesture Recognition, 2015 
//
//       Constrained Local Neural Fields for robust facial landmark detection in the wild.
//       Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency. 
//       in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.    
//
///////////////////////////////////////////////////////////////////////////////

#ifndef __SVMSTATICLIN_h_
#define __SVMSTATICLIN_h_

#include <vector>
#include <string>

#include <stdio.h>
#include <iostream>
#include <fstream>

#include <opencv2/core/core.hpp>

namespace FaceAnalysis
{

// Collection of linear SVR regressors for AU prediction
class SVM_static_lin{

public:

	SVM_static_lin()
	{}

	// Predict the AU from HOG appearance of the face
	void Predict(std::vector<double>& predictions, std::vector<std::string>& names, const cv::Mat_<double>& fhog_descriptor, const cv::Mat_<double>& geom_params);

	// Reading in the model (or adding to it)
	void Read(std::ifstream& stream, const std::vector<std::string>& au_names);

	std::vector<std::string> GetAUNames() const
	{
		return AU_names;
	}

private:

	// The names of Action Units this model is responsible for
	std::vector<std::string> AU_names;

	// For normalisation
	cv::Mat_<double> means;
	
	// For actual prediction
	cv::Mat_<double> support_vectors;	
	cv::Mat_<double> biases;

	std::vector<double> pos_classes;
	std::vector<double> neg_classes;

};
  //===========================================================================
}
#endif