105 lines
3.6 KiB
C++
105 lines
3.6 KiB
C++
///////////////////////////////////////////////////////////////////////////////
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// Copyright (C) 2017, Carnegie Mellon University and University of Cambridge,
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// all rights reserved.
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//
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// ACADEMIC OR NON-PROFIT ORGANIZATION NONCOMMERCIAL RESEARCH USE ONLY
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//
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// BY USING OR DOWNLOADING THE SOFTWARE, YOU ARE AGREEING TO THE TERMS OF THIS LICENSE AGREEMENT.
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// IF YOU DO NOT AGREE WITH THESE TERMS, YOU MAY NOT USE OR DOWNLOAD THE SOFTWARE.
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//
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// License can be found in OpenFace-license.txt
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//
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// * Any publications arising from the use of this software, including but
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// not limited to academic journal and conference publications, technical
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// reports and manuals, must cite at least one of the following works:
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//
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// OpenFace: an open source facial behavior analysis toolkit
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// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency
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// in IEEE Winter Conference on Applications of Computer Vision, 2016
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//
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// Rendering of Eyes for Eye-Shape Registration and Gaze Estimation
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// Erroll Wood, Tadas Baltrušaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
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// in IEEE International. Conference on Computer Vision (ICCV), 2015
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//
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// Cross-dataset learning and person-speci?c normalisation for automatic Action Unit detection
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// Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson
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// in Facial Expression Recognition and Analysis Challenge,
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// IEEE International Conference on Automatic Face and Gesture Recognition, 2015
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//
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// Constrained Local Neural Fields for robust facial landmark detection in the wild.
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// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency.
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// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
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//
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///////////////////////////////////////////////////////////////////////////////
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// Parameters of the Face analyser
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#ifndef __FACE_ANALYSER_PARAM_H
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#define __FACE_ANALYSER_PARAM_H
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#include <vector>
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#include <opencv2/core/core.hpp>
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// Boost includes
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#include <filesystem.hpp>
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#include <filesystem/fstream.hpp>
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using namespace std;
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namespace FaceAnalysis
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{
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struct FaceAnalyserParameters
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{
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public:
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// Constructors
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FaceAnalyserParameters();
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FaceAnalyserParameters(string root_exe);
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FaceAnalyserParameters(vector<string> &arguments);
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// These are the parameters of training and will not change and are fixed
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const double sim_scale_au = 0.7;
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const int sim_size_au = 112;
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// Should the output aligned faces be grayscale
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bool grayscale;
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// Use getters and setters for these as they might need to reload models and make sure the scale and size ratio makes sense
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void setAlignedOutput(int output_size, double scale=-1, bool masked = true);
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// This will also change the model location
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void OptimizeForVideos();
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void OptimizeForImages();
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double getAlignMask() const { return sim_align_face_mask; }
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double getSimScaleOut() const { return sim_scale_out; }
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int getSimSizeOut() const { return sim_size_out; }
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bool getDynamic() const { return dynamic; }
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string getModelLoc() const { return string(model_location); }
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vector<cv::Vec3d> getOrientationBins() const { return vector<cv::Vec3d>(orientation_bins); }
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private:
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void init();
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// Aligned face output size
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double sim_scale_out;
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int sim_size_out;
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// Should aligned face be masked out from background
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bool sim_align_face_mask;
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// Should a video stream be assumed
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bool dynamic;
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// Where to load the models from
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string model_location;
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// The location of the executable
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boost::filesystem::path root;
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vector<cv::Vec3d> orientation_bins;
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};
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}
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#endif // __FACE_ANALYSER_PARAM_H
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