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* Travis OpenCV4 update, testing Ubuntu with new OpenCV * Fix to Ubuntu travis * Another attempt at OpenCV 4.0 for Ubuntu * And another OpenCV attempt. * Simplifying the travis script * Ubuntu OpenCV 4 support. * Updating to OpenCV 4, for x64 windows. * Fixes to move to OpenCV 4 on windows. * Travis fix for OpenCV 4 on OSX * Renaming a lib. * Travis opencv4 fix. * Building OpenCV4 versions using appveyor. * Attempt mac travis fix. * Small travis fix. * Travis fix attempt. * First iteration in boost removal and upgrade to C++17 * Test with ocv 4.0 * Moving filesystem out of stdafx * Some more boost testing with cmake. * More CMAKE options * More compiler flag changes * Another attempt at compiler options. * Another attempt. * More filesystem stuff. * Linking to filesystem. * Cmake fix with target linking. * Attempting travis with g++-8 * Attempting to setup g++8 on travis linux. * Another travis change. * Adding OpenBLAS to travis and removing g++-8 * Fixing typo * More travis experiments. * More travis debugging. * A small directory change. * Adding some more travis changes. * travis typo fix. * Some reordering of travis, for cleaner yml * Removing `using namespace std` in order to avoid clash with byte and to make the code more consistent. * Working towards removing std::filesystem requirement, allow boost::filesystem as well. * Making boost an optional dependency * Fixing std issue. * Fixing cmake issue. * Fixing the precompiled header issue. * Another cmake boost fix. * Including missing files. * Removing unnecessary includes. * Removing more includes. * Changes to appveyor build, proper removal of VS2015 * If boost is present, do not need to link to filesystem. * Removing un-needed link library. * oops * Mac attempt at opencv4 travis. * Upgrading OCV to 4.1 on VS2018 * Downloading OpenCV binaries through a script * Triger an appveyor build. * Upgrading VS version. * Attempting VS2017 build * Adding win-32 libraries for OpenCV 4.1 * Adding OpenCV 32 bit libraries.
98 lines
3.5 KiB
C++
98 lines
3.5 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 2.0: Facial Behavior Analysis Toolkit
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// Tadas Baltrušaitis, Amir Zadeh, Yao Chong Lim, and Louis-Philippe Morency
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// in IEEE International Conference on Automatic Face and Gesture Recognition, 2018
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//
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// Convolutional experts constrained local model for facial landmark detection.
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// A. Zadeh, T. Baltrušaitis, and Louis-Philippe Morency,
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// in Computer Vision and Pattern Recognition Workshops, 2017.
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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-specific 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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///////////////////////////////////////////////////////////////////////////////
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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 <stdafx_fa.h>
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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(std::string root_exe);
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FaceAnalyserParameters(std::vector<std::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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bool 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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std::string getModelLoc() const { return std::string(model_location); }
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std::vector<cv::Vec3d> getOrientationBins() const { return std::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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std::string model_location;
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// The location of the executable
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fs::path root;
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std::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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