sustaining_gazes/lib/local/CppInerop/FaceAnalyserInterop.h

475 lines
15 KiB
C++
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2016, Carnegie Mellon University and University of Cambridge,
// all rights reserved.
//
// THIS SOFTWARE IS PROVIDED “AS IS” FOR ACADEMIC USE ONLY AND ANY EXPRESS
// OR IMPLIED WARRANTIES WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
// THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 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.
//
// Notwithstanding the license granted herein, Licensee acknowledges that certain components
// of the Software may be covered by so-called “open source” software licenses (“Open Source
// Components”), which means any software licenses approved as open source licenses by the
// Open Source Initiative or any substantially similar licenses, including without limitation any
// license that, as a condition of distribution of the software licensed under such license,
// requires that the distributor make the software available in source code format. Licensor shall
// provide a list of Open Source Components for a particular version of the Software upon
// Licensees request. Licensee will comply with the applicable terms of such licenses and to
// the extent required by the licenses covering Open Source Components, the terms of such
// licenses will apply in lieu of the terms of this Agreement. To the extent the terms of the
// licenses applicable to Open Source Components prohibit any of the restrictions in this
// License Agreement with respect to such Open Source Component, such restrictions will not
// apply to such Open Source Component. To the extent the terms of the licenses applicable to
// Open Source Components require Licensor to make an offer to provide source code or
// related information in connection with the Software, such offer is hereby made. Any request
// for source code or related information should be directed to cl-face-tracker-distribution@lists.cam.ac.uk
// Licensee acknowledges receipt of notices for the Open Source Components for the initial
// delivery of the Software.
// * 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.
//
///////////////////////////////////////////////////////////////////////////////
// FaceAnalyser_Interop.h
#ifndef __FACE_ANALYSER_INTEROP_h_
#define __FACE_ANALYSER_INTEROP_h_
#pragma once
// Include all the unmanaged things we need.
#pragma managed
#include <msclr\marshal.h>
#include <msclr\marshal_cppstd.h>
#pragma unmanaged
#include <opencv2/core/core.hpp>
#include "opencv2/objdetect.hpp"
#include "opencv2/calib3d.hpp"
#include <opencv2/imgcodecs.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <OpenCVWrappers.h>
#include <LandmarkDetectorInterop.h>
#include <Face_utils.h>
#include <FaceAnalyser.h>
#include <GazeEstimation.h>
// Allows to overcome boost name clash stuff with C++ CLI
#ifdef __cplusplus_cli
#define generic __identifier(generic)
#endif
// Boost stuff
#include <filesystem.hpp>
#include <filesystem/fstream.hpp>
#ifdef __cplusplus_cli
#undef generic
#endif
#pragma managed
namespace FaceAnalyser_Interop {
public ref class FaceAnalyserManaged
{
private:
FaceAnalysis::FaceAnalyser* face_analyser;
// The actual descriptors (for visualisation and output)
cv::Mat_<double>* hog_features;
cv::Mat* aligned_face;
cv::Mat* visualisation;
cv::Mat* tracked_face;
// Variables used for recording things
std::ofstream* hog_output_file;
std::string* align_output_dir;
int* num_rows;
int* num_cols;
bool* good_frame;
cv::VideoWriter* tracked_vid_writer;
// Variable storing gaze for recording
// Absolute gaze direction
cv::Point3f* gazeDirection0;
cv::Point3f* gazeDirection1;
cv::Point3f* pupil_left;
cv::Point3f* pupil_right;
public:
FaceAnalyserManaged(System::String^ root, bool dynamic)
{
vector<cv::Vec3d> orientation_bins;
orientation_bins.push_back(cv::Vec3d(0,0,0));
double scale = 0.7;
int width = 112;
int height = 112;
string root_std = msclr::interop::marshal_as<std::string>(root);
// TODO diff paths and locations for the demo mode
boost::filesystem::path tri_loc = boost::filesystem::path(root_std) / "model" / "tris_68_full.txt";
boost::filesystem::path au_loc;
if(dynamic)
{
au_loc = boost::filesystem::path(root_std) / "AU_predictors" / "AU_all_best.txt";
}
else
{
au_loc = boost::filesystem::path(root_std) / "AU_predictors" / "AU_all_static.txt";
}
face_analyser = new FaceAnalysis::FaceAnalyser(orientation_bins, scale, width, height, au_loc.string(), tri_loc.string());
hog_features = new cv::Mat_<double>();
aligned_face = new cv::Mat();
visualisation = new cv::Mat();
tracked_face = new cv::Mat();
num_rows = new int;
num_cols = new int;
good_frame = new bool;
align_output_dir = new string();
hog_output_file = new std::ofstream();
gazeDirection0 = new cv::Point3f();
gazeDirection1 = new cv::Point3f();
pupil_left = new cv::Point3f();
pupil_right = new cv::Point3f();
}
void SetupAlignedImageRecording(System::String^ directory)
{
*align_output_dir = msclr::interop::marshal_as<std::string>(directory);
}
void SetupHOGRecording(System::String^ file)
{
// Create the file for recording
hog_output_file->open(msclr::interop::marshal_as<std::string>(file), ios_base::out | ios_base::binary);
}
void SetupTrackingRecording(System::String^ file, int width, int height, double fps)
{
tracked_vid_writer = new cv::VideoWriter(msclr::interop::marshal_as<std::string>(file), CV_FOURCC('D', 'I', 'V', 'X'), fps, cv::Size(width, height));
}
void StopHOGRecording()
{
hog_output_file->close();
}
void StopTrackingRecording()
{
tracked_vid_writer->release();
}
void RecordAlignedFrame(int frame_num)
{
char name[100];
// output the frame number
sprintf(name, "frame_det_%06d.png", frame_num);
string out_file = (boost::filesystem::path(*align_output_dir) / boost::filesystem::path(name)).string();
imwrite(out_file, *aligned_face);
}
void RecordHOGFrame()
{
// Using FHOGs, hence 31 channels
int num_channels = 31;
hog_output_file->write((char*)(num_cols), 4);
hog_output_file->write((char*)(num_rows), 4);
hog_output_file->write((char*)(&num_channels), 4);
// Not the best way to store a bool, but will be much easier to read it
float good_frame_float;
if(good_frame)
good_frame_float = 1;
else
good_frame_float = -1;
hog_output_file->write((char*)(&good_frame_float), 4);
cv::MatConstIterator_<double> descriptor_it = hog_features->begin();
for(int y = 0; y < *num_cols; ++y)
{
for(int x = 0; x < *num_rows; ++x)
{
for(unsigned int o = 0; o < 31; ++o)
{
float hog_data = (float)(*descriptor_it++);
hog_output_file->write((char*)&hog_data, 4);
}
}
}
}
void RecordTrackedFace()
{
tracked_vid_writer->write(*tracked_face);
}
void AddNextFrame(OpenCVWrappers::RawImage^ frame, CppInterop::LandmarkDetector::CLNF^ clnf, double fx, double fy, double cx, double cy, bool online, bool vis_hog, bool vis_tracked) {
face_analyser->AddNextFrame(frame->Mat, *clnf->getCLNF(), 0, online, vis_hog);
face_analyser->GetLatestHOG(*hog_features, *num_rows, *num_cols);
face_analyser->GetLatestAlignedFace(*aligned_face);
*good_frame = clnf->clnf->detection_success;
if(vis_hog)
{
*visualisation = face_analyser->GetLatestHOGDescriptorVisualisation();
}
if(vis_tracked)
{
if(frame->Mat.cols != tracked_face->cols && frame->Mat.rows != tracked_face->rows)
{
*tracked_face = frame->Mat.clone();
}
else
{
frame->Mat.clone().copyTo(*tracked_face);
}
if(clnf->clnf->detection_success)
{
::LandmarkDetector::Draw(*tracked_face, *clnf->clnf);
}
tracked_face->deallocate();
}
// After the AUs have been detected do some gaze estimation as well
FaceAnalysis::EstimateGaze(*clnf->getCLNF(), *gazeDirection0, fx, fy, cx, cy, true);
FaceAnalysis::EstimateGaze(*clnf->getCLNF(), *gazeDirection1, fx, fy, cx, cy, false);
// Grab pupil locations
int part_left = -1;
int part_right = -1;
for (size_t i = 0; i < clnf->getCLNF()->hierarchical_models.size(); ++i)
{
if (clnf->getCLNF()->hierarchical_model_names[i].compare("left_eye_28") == 0)
{
part_left = i;
}
if (clnf->getCLNF()->hierarchical_model_names[i].compare("right_eye_28") == 0)
{
part_right = i;
}
}
cv::Mat_<double> eyeLdmks3d_left = clnf->getCLNF()->hierarchical_models[part_left].GetShape(fx, fy, cx, cy);
cv::Point3f pupil_left_h = FaceAnalysis::GetPupilPosition(eyeLdmks3d_left);
pupil_left->x = pupil_left_h.x; pupil_left->y = pupil_left_h.y; pupil_left->z = pupil_left_h.z;
cv::Mat_<double> eyeLdmks3d_right = clnf->getCLNF()->hierarchical_models[part_right].GetShape(fx, fy, cx, cy);
cv::Point3f pupil_right_h = FaceAnalysis::GetPupilPosition(eyeLdmks3d_right);
pupil_right->x = pupil_right_h.x; pupil_right->y = pupil_right_h.y; pupil_right->z = pupil_right_h.z;
}
System::Tuple<System::Tuple<double, double, double>^, System::Tuple<double, double, double>^>^ GetGazeCamera()
{
auto gaze0 = gcnew System::Tuple<double, double, double>(gazeDirection0->x, gazeDirection0->y, gazeDirection0->z);
auto gaze1 = gcnew System::Tuple<double, double, double>(gazeDirection1->x, gazeDirection1->y, gazeDirection1->z);
return gcnew System::Tuple<System::Tuple<double, double, double>^, System::Tuple<double, double, double>^>(gaze0, gaze1);
}
System::Collections::Generic::List<System::Tuple<System::Windows::Point, System::Windows::Point>^>^ CalculateGazeLines(double scale, float fx, float fy, float cx, float cy)
{
cv::Mat_<double> cameraMat = (cv::Mat_<double>(3, 3) << fx, 0, cx, 0, fy, cy, 0, 0, 0);
vector<cv::Point3f> points_left;
points_left.push_back(cv::Point3f(*pupil_left));
points_left.push_back(cv::Point3f(*pupil_left + *gazeDirection0 * 40.0 * scale));
vector<cv::Point3f> points_right;
points_right.push_back(cv::Point3f(*pupil_right));
points_right.push_back(cv::Point3f(*pupil_right + *gazeDirection1 * 40.0 * scale));
// Perform manual projection of points
vector<cv::Point2d> imagePoints_left;
for (int i = 0; i < points_left.size(); ++i)
{
double x = points_left[i].x * fx / points_left[i].z + cx;
double y = points_left[i].y * fy / points_left[i].z + cy;
imagePoints_left.push_back(cv::Point2d(x, y));
}
vector<cv::Point2d> imagePoints_right;
for (int i = 0; i < points_right.size(); ++i)
{
double x = points_right[i].x * fx / points_right[i].z + cx;
double y = points_right[i].y * fy / points_right[i].z + cy;
imagePoints_right.push_back(cv::Point2d(x, y));
}
auto lines = gcnew System::Collections::Generic::List<System::Tuple<System::Windows::Point, System::Windows::Point>^>();
lines->Add(gcnew System::Tuple<System::Windows::Point, System::Windows::Point>(System::Windows::Point(imagePoints_left[0].x, imagePoints_left[0].y), System::Windows::Point(imagePoints_left[1].x, imagePoints_left[1].y)));
lines->Add(gcnew System::Tuple<System::Windows::Point, System::Windows::Point>(System::Windows::Point(imagePoints_right[0].x, imagePoints_right[0].y), System::Windows::Point(imagePoints_right[1].x, imagePoints_right[1].y)));
return lines;
}
System::Collections::Generic::List<System::String^>^ GetClassActionUnitsNames()
{
auto names = face_analyser->GetAUClassNames();
auto names_ret = gcnew System::Collections::Generic::List<System::String^>();
for(std::string name : names)
{
names_ret->Add(gcnew System::String(name.c_str()));
}
return names_ret;
}
System::Collections::Generic::List<System::String^>^ GetRegActionUnitsNames()
{
auto names = face_analyser->GetAURegNames();
auto names_ret = gcnew System::Collections::Generic::List<System::String^>();
for(std::string name : names)
{
names_ret->Add(gcnew System::String(name.c_str()));
}
return names_ret;
}
System::Collections::Generic::Dictionary<System::String^, double>^ GetCurrentAUsClass()
{
auto classes = face_analyser->GetCurrentAUsClass();
auto au_classes = gcnew System::Collections::Generic::Dictionary<System::String^, double>();
for(auto p: classes)
{
au_classes->Add(gcnew System::String(p.first.c_str()), p.second);
}
return au_classes;
}
System::Collections::Generic::Dictionary<System::String^, double>^ GetCurrentAUsReg()
{
auto preds = face_analyser->GetCurrentAUsReg();
auto au_preds = gcnew System::Collections::Generic::Dictionary<System::String^, double>();
for(auto p: preds)
{
au_preds->Add(gcnew System::String(p.first.c_str()), p.second);
}
return au_preds;
}
OpenCVWrappers::RawImage^ GetLatestAlignedFace() {
OpenCVWrappers::RawImage^ face_aligned_image = gcnew OpenCVWrappers::RawImage(*aligned_face);
return face_aligned_image;
}
OpenCVWrappers::RawImage^ GetLatestHOGDescriptorVisualisation() {
OpenCVWrappers::RawImage^ HOG_vis_image = gcnew OpenCVWrappers::RawImage(*visualisation);
return HOG_vis_image;
}
void Reset()
{
face_analyser->Reset();
}
// Finalizer. Definitely called before Garbage Collection,
// but not automatically called on explicit Dispose().
// May be called multiple times.
!FaceAnalyserManaged()
{
delete hog_features;
delete aligned_face;
delete visualisation;
delete num_cols;
delete num_rows;
delete hog_output_file;
delete good_frame;
delete align_output_dir;
delete face_analyser;
delete tracked_face;
delete gazeDirection0;
delete gazeDirection1;
delete pupil_left;
delete pupil_right;
if(tracked_vid_writer != 0)
{
delete tracked_vid_writer;
}
}
// Destructor. Called on explicit Dispose() only.
~FaceAnalyserManaged()
{
this->!FaceAnalyserManaged();
}
};
}
#endif