sustaining_gazes/lib/local/LandmarkDetector/src/LandmarkDetectorParameters.cpp

271 lines
7.1 KiB
C++

///////////////////////////////////////////////////////////////////////////////
// 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.
//
///////////////////////////////////////////////////////////////////////////////
#include "stdafx.h"
#include "LandmarkDetectorParameters.h"
// Boost includes
#include <filesystem.hpp>
#include <filesystem/fstream.hpp>
// System includes
#include <sstream>
#include <iostream>
#include <cstdlib>
#ifndef CONFIG_DIR
#define CONFIG_DIR "~"
#endif
using namespace std;
using namespace LandmarkDetector;
FaceModelParameters::FaceModelParameters()
{
// initialise the default values
init();
}
FaceModelParameters::FaceModelParameters(vector<string> &arguments)
{
// initialise the default values
init();
// First element is reserved for the executable location (useful for finding relative model locs)
boost::filesystem::path root = boost::filesystem::path(arguments[0]).parent_path();
bool* valid = new bool[arguments.size()];
valid[0] = true;
for (size_t i = 1; i < arguments.size(); ++i)
{
valid[i] = true;
if (arguments[i].compare("-mloc") == 0)
{
string model_loc = arguments[i + 1];
model_location = model_loc;
valid[i] = false;
valid[i + 1] = false;
i++;
}
if (arguments[i].compare("-sigma") == 0)
{
stringstream data(arguments[i + 1]);
data >> sigma;
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-w_reg") == 0)
{
stringstream data(arguments[i + 1]);
data >> weight_factor;
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-reg") == 0)
{
stringstream data(arguments[i + 1]);
data >> reg_factor;
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-multi_view") == 0)
{
stringstream data(arguments[i + 1]);
int m_view;
data >> m_view;
multi_view = (bool)(m_view != 0);
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-validate_detections") == 0)
{
stringstream data(arguments[i + 1]);
int v_det;
data >> v_det;
validate_detections = (bool)(v_det != 0);
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-n_iter") == 0)
{
stringstream data(arguments[i + 1]);
data >> num_optimisation_iteration;
valid[i] = false;
valid[i + 1] = false;
i++;
}
else if (arguments[i].compare("-gaze") == 0)
{
track_gaze = true;
valid[i] = false;
i++;
}
else if (arguments[i].compare("-q") == 0)
{
quiet_mode = true;
valid[i] = false;
}
else if (arguments[i].compare("-wild") == 0)
{
// For in the wild fitting these parameters are suitable
window_sizes_init = vector<int>(4);
window_sizes_init[0] = 15; window_sizes_init[1] = 13; window_sizes_init[2] = 11; window_sizes_init[3] = 9;
sigma = 1.25;
reg_factor = 35;
weight_factor = 2.5;
num_optimisation_iteration = 10;
valid[i] = false;
// For in-the-wild images use an in-the wild detector
curr_face_detector = HOG_SVM_DETECTOR;
}
}
for (int i = (int)arguments.size() - 1; i >= 0; --i)
{
if (!valid[i])
{
arguments.erase(arguments.begin() + i);
}
}
// Make sure model_location is valid
// First check working directory, then the executable's directory, then the config path set by the build process.
boost::filesystem::path config_path = boost::filesystem::path(CONFIG_DIR);
boost::filesystem::path model_path = boost::filesystem::path(model_location);
if (boost::filesystem::exists(model_path))
{
model_location = model_path.string();
}
else if (boost::filesystem::exists(root/model_path))
{
model_location = (root/model_path).string();
}
else if (boost::filesystem::exists(config_path/model_path))
{
model_location = (config_path/model_path).string();
}
else
{
std::cout << "Could not find the landmark detection model to load" << std::endl;
}
}
void FaceModelParameters::init()
{
// number of iterations that will be performed at each scale
num_optimisation_iteration = 5;
// using an external face checker based on SVM
validate_detections = true;
// Using hierarchical refinement by default (can be turned off)
refine_hierarchical = true;
// Refining parameters by default
refine_parameters = true;
window_sizes_small = vector<int>(4);
window_sizes_init = vector<int>(4);
// For fast tracking
window_sizes_small[0] = 0;
window_sizes_small[1] = 9;
window_sizes_small[2] = 7;
window_sizes_small[3] = 5;
// Just for initialisation
window_sizes_init.at(0) = 11;
window_sizes_init.at(1) = 9;
window_sizes_init.at(2) = 7;
window_sizes_init.at(3) = 5;
face_template_scale = 0.3;
// Off by default (as it might lead to some slight inaccuracies in slowly moving faces)
use_face_template = false;
// For first frame use the initialisation
window_sizes_current = window_sizes_init;
model_location = "model/main_clnf_general.txt";
sigma = 1.5;
reg_factor = 25;
weight_factor = 0; // By default do not use NU-RLMS for videos as it does not work as well for them
validation_boundary = -0.45;
limit_pose = true;
multi_view = false;
reinit_video_every = 4;
// Face detection
#if OS_UNIX
face_detector_location = "classifiers/haarcascade_frontalface_alt.xml";
#else
face_detector_location = "classifiers/haarcascade_frontalface_alt.xml";
#endif
quiet_mode = false;
// By default use HOG SVM
curr_face_detector = HOG_SVM_DETECTOR;
// The gaze tracking has to be explicitly initialised
track_gaze = false;
}