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sustaining_gazes/lib/local/CppInerop/LandmarkDetectorInterop.h
Tadas Baltrusaitis f98ae0747e Big restructure of the code, moving closer to a new version with a GUI: 
- Adding a new boost version (1.63)
- Decoupling FaceAnalyser from LandmarkDetector
- FaceAnalyser is much easier to load with a parameters class
- Moving GazeAnalyser as a separate library
- GUI now uses new FaceAnalyser, LandmarkDetector, and GazeAnalyser
2017-05-18 17:04:38 -04:00

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///////////////////////////////////////////////////////////////////////////////
// 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 __LANDMARK_DETECTOR_INTEROP_h_
#define __LANDMARK_DETECTOR_INTEROP_h_
#pragma once
#pragma managed
#include <msclr\marshal.h>
#include <msclr\marshal_cppstd.h>
#pragma unmanaged
// Include all the unmanaged things we need.
#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>
// Allows to overcome boost name clash stuff with C++ CLI
#ifdef __cplusplus_cli
#define generic __identifier(generic)
#endif
#include <OpenCVWrappers.h>
#include <LandmarkCoreIncludes.h>
#include <Face_utils.h>
#include <FaceAnalyser.h>
#ifdef __cplusplus_cli
#undef generic
#endif
#pragma managed
namespace CppInterop {
namespace LandmarkDetector {
public ref class FaceModelParameters
{
public:
::LandmarkDetector::FaceModelParameters* params;
public:
// Initialise the parameters
FaceModelParameters(System::String^ root, bool demo)
{
std::string root_std = msclr::interop::marshal_as<std::string>(root);
vector<std::string> args;
args.push_back(root_std);
params = new ::LandmarkDetector::FaceModelParameters(args);
if(demo)
{
params->model_location = "model/main_clnf_demos.txt";
}
params->track_gaze = true;
}
// TODO this could have optimize for demo mode (also could appropriately update sigma, reg_factor as well)
void optimiseForVideo()
{
params->window_sizes_small = vector<int>(4);
params->window_sizes_init = vector<int>(4);
// For fast tracking
params->window_sizes_small[0] = 0;
params->window_sizes_small[1] = 9;
params->window_sizes_small[2] = 7;
params->window_sizes_small[3] = 5;
// Just for initialisation
params->window_sizes_init.at(0) = 11;
params->window_sizes_init.at(1) = 9;
params->window_sizes_init.at(2) = 7;
params->window_sizes_init.at(3) = 5;
// For first frame use the initialisation
params->window_sizes_current = params->window_sizes_init;
params->multi_view = false;
params->num_optimisation_iteration = 5;
params->sigma = 1.5;
params->reg_factor = 25;
params->weight_factor = 0;
}
void optimiseForImages()
{
params->window_sizes_init = vector<int>(4);
params->window_sizes_init[0] = 15;
params->window_sizes_init[1] = 13;
params->window_sizes_init[2] = 11;
params->window_sizes_init[3] = 9;
params->multi_view = true;
params->sigma = 1.25;
params->reg_factor = 35;
params->weight_factor = 2.5;
params->num_optimisation_iteration = 10;
}
::LandmarkDetector::FaceModelParameters* getParams() {
return params;
}
~FaceModelParameters()
{
delete params;
}
};
public ref class CLNF
{
public:
// A pointer to the CLNF landmark detector
::LandmarkDetector::CLNF* clnf;
public:
// Wrapper functions for the relevant CLNF functionality
CLNF() : clnf(new ::LandmarkDetector::CLNF()) { }
CLNF(FaceModelParameters^ params)
{
clnf = new ::LandmarkDetector::CLNF(params->getParams()->model_location);
}
~CLNF()
{
delete clnf;
}
::LandmarkDetector::CLNF* getCLNF() {
return clnf;
}
void Reset() {
clnf->Reset();
}
void Reset(double x, double y) {
clnf->Reset(x, y);
}
double GetConfidence()
{
return clnf->detection_certainty;
}
bool DetectLandmarksInVideo(OpenCVWrappers::RawImage^ image, FaceModelParameters^ modelParams) {
return ::LandmarkDetector::DetectLandmarksInVideo(image->Mat, *clnf, *modelParams->getParams());
}
bool DetectFaceLandmarksInImage(OpenCVWrappers::RawImage^ image, FaceModelParameters^ modelParams) {
return ::LandmarkDetector::DetectLandmarksInImage(image->Mat, *clnf, *modelParams->getParams());
}
System::Collections::Generic::List<System::Collections::Generic::List<System::Tuple<double,double>^>^>^ DetectMultiFaceLandmarksInImage(OpenCVWrappers::RawImage^ image, FaceModelParameters^ modelParams) {
auto all_landmarks = gcnew System::Collections::Generic::List<System::Collections::Generic::List<System::Tuple<double,double>^>^>();
// Detect faces in an image
vector<cv::Rect_<double> > face_detections;
vector<double> confidences;
// TODO this should be pre-allocated as now it might be a bit too slow
dlib::frontal_face_detector face_detector_hog = dlib::get_frontal_face_detector();
::LandmarkDetector::DetectFacesHOG(face_detections, image->Mat, face_detector_hog, confidences);
// Detect landmarks around detected faces
int face_det = 0;
// perform landmark detection for every face detected
for(size_t face=0; face < face_detections.size(); ++face)
{
cv::Mat depth;
// if there are multiple detections go through them
bool success = ::LandmarkDetector::DetectLandmarksInImage(image->Mat, depth, face_detections[face], *clnf, *modelParams->getParams());
auto landmarks_curr = gcnew System::Collections::Generic::List<System::Tuple<double,double>^>();
if(clnf->detected_landmarks.cols == 1)
{
int n = clnf->detected_landmarks.rows / 2;
for(int i = 0; i < n; ++i)
{
landmarks_curr->Add(gcnew System::Tuple<double,double>(clnf->detected_landmarks.at<double>(i,0), clnf->detected_landmarks.at<double>(i+n,0)));
}
}
else
{
int n = clnf->detected_landmarks.cols / 2;
for(int i = 0; i < clnf->detected_landmarks.cols; ++i)
{
landmarks_curr->Add(gcnew System::Tuple<double,double>(clnf->detected_landmarks.at<double>(0,i), clnf->detected_landmarks.at<double>(0,i+1)));
}
}
all_landmarks->Add(landmarks_curr);
}
return all_landmarks;
}
void GetPoseWRTCamera(System::Collections::Generic::List<double>^ pose, double fx, double fy, double cx, double cy) {
auto pose_vec = ::LandmarkDetector::GetPoseWRTCamera(*clnf, fx, fy, cx, cy);
pose->Clear();
for(int i = 0; i < 6; ++i)
{
pose->Add(pose_vec[i]);
}
}
void GetPose(System::Collections::Generic::List<double>^ pose, double fx, double fy, double cx, double cy) {
auto pose_vec = ::LandmarkDetector::GetPose(*clnf, fx, fy, cx, cy);
pose->Clear();
for(int i = 0; i < 6; ++i)
{
pose->Add(pose_vec[i]);
}
}
System::Collections::Generic::List<System::Tuple<double,double>^>^ CalculateVisibleLandmarks() {
vector<cv::Point2d> vecLandmarks = ::LandmarkDetector::CalculateVisibleLandmarks(*clnf);
auto landmarks = gcnew System::Collections::Generic::List<System::Tuple<double,double>^>();
for(cv::Point2d p : vecLandmarks) {
landmarks->Add(gcnew System::Tuple<double,double>(p.x, p.y));
}
return landmarks;
}
System::Collections::Generic::List<System::Tuple<double, double>^>^ CalculateAllLandmarks() {
vector<cv::Point2d> vecLandmarks = ::LandmarkDetector::CalculateAllLandmarks(*clnf);
auto landmarks = gcnew System::Collections::Generic::List<System::Tuple<double, double>^>();
for (cv::Point2d p : vecLandmarks) {
landmarks->Add(gcnew System::Tuple<double, double>(p.x, p.y));
}
return landmarks;
}
System::Collections::Generic::List<System::Tuple<double, double>^>^ CalculateAllEyeLandmarks() {
vector<cv::Point2d> vecLandmarks = ::LandmarkDetector::CalculateAllEyeLandmarks(*clnf);
auto landmarks = gcnew System::Collections::Generic::List<System::Tuple<double, double>^>();
for (cv::Point2d p : vecLandmarks) {
landmarks->Add(gcnew System::Tuple<double, double>(p.x, p.y));
}
return landmarks;
}
System::Collections::Generic::List<System::Tuple<double, double>^>^ CalculateVisibleEyeLandmarks() {
vector<cv::Point2d> vecLandmarks = ::LandmarkDetector::CalculateVisibleEyeLandmarks(*clnf);
auto landmarks = gcnew System::Collections::Generic::List<System::Tuple<double, double>^>();
for (cv::Point2d p : vecLandmarks) {
landmarks->Add(gcnew System::Tuple<double, double>(p.x, p.y));
}
return landmarks;
}
System::Collections::Generic::List<System::Windows::Media::Media3D::Point3D>^ Calculate3DLandmarks(double fx, double fy, double cx, double cy) {
cv::Mat_<double> shape3D = clnf->GetShape(fx, fy, cx, cy);
auto landmarks_3D = gcnew System::Collections::Generic::List<System::Windows::Media::Media3D::Point3D>();
for(int i = 0; i < shape3D.cols; ++i)
{
landmarks_3D->Add(System::Windows::Media::Media3D::Point3D(shape3D.at<double>(0, i), shape3D.at<double>(1, i), shape3D.at<double>(2, i)));
}
return landmarks_3D;
}
// Static functions from the LandmarkDetector namespace.
void DrawLandmarks(OpenCVWrappers::RawImage^ img, System::Collections::Generic::List<System::Windows::Point>^ landmarks) {
vector<cv::Point> vecLandmarks;
for(int i = 0; i < landmarks->Count; i++) {
System::Windows::Point p = landmarks[i];
vecLandmarks.push_back(cv::Point(p.X, p.Y));
}
::LandmarkDetector::DrawLandmarks(img->Mat, vecLandmarks);
}
System::Collections::Generic::List<System::Tuple<System::Windows::Point, System::Windows::Point>^>^ CalculateBox(float fx, float fy, float cx, float cy) {
cv::Vec6d pose = ::LandmarkDetector::GetPose(*clnf, fx,fy, cx, cy);
vector<pair<cv::Point2d, cv::Point2d>> vecLines = ::LandmarkDetector::CalculateBox(pose, fx, fy, cx, cy);
auto lines = gcnew System::Collections::Generic::List<System::Tuple<System::Windows::Point,System::Windows::Point>^>();
for(pair<cv::Point2d, cv::Point2d> line : vecLines) {
lines->Add(gcnew System::Tuple<System::Windows::Point, System::Windows::Point>(System::Windows::Point(line.first.x, line.first.y), System::Windows::Point(line.second.x, line.second.y)));
}
return lines;
}
void DrawBox(System::Collections::Generic::List<System::Tuple<System::Windows::Point, System::Windows::Point>^>^ lines, OpenCVWrappers::RawImage^ image, double r, double g, double b, int thickness) {
cv::Scalar color = cv::Scalar(r,g,b,1);
vector<pair<cv::Point, cv::Point>> vecLines;
for(int i = 0; i < lines->Count; i++) {
System::Tuple<System::Windows::Point, System::Windows::Point>^ points = lines[i];
vecLines.push_back(pair<cv::Point, cv::Point>(cv::Point(points->Item1.X, points->Item1.Y), cv::Point(points->Item2.X, points->Item2.Y)));
}
::LandmarkDetector::DrawBox(vecLines, image->Mat, color, thickness);
}
int GetNumPoints()
{
return clnf->pdm.NumberOfPoints();
}
int GetNumModes()
{
return clnf->pdm.NumberOfModes();
}
// Getting the non-rigid shape parameters describing the facial expression
System::Collections::Generic::List<double>^ GetNonRigidParams()
{
auto non_rigid_params = gcnew System::Collections::Generic::List<double>();
for (int i = 0; i < clnf->params_local.rows; ++i)
{
non_rigid_params->Add(clnf->params_local.at<double>(i));
}
return non_rigid_params;
}
// Getting the rigid shape parameters describing face scale rotation and translation (scale,rotx,roty,rotz,tx,ty)
System::Collections::Generic::List<double>^ GetRigidParams()
{
auto rigid_params = gcnew System::Collections::Generic::List<double>();
for (size_t i = 0; i < 6; ++i)
{
rigid_params->Add(clnf->params_global[i]);
}
return rigid_params;
}
// Rigid params followed by non-rigid ones
System::Collections::Generic::List<double>^ GetParams()
{
auto all_params = GetRigidParams();
all_params->AddRange(GetNonRigidParams());
return all_params;
}
};
}
}
#endif
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