411 lines
No EOL
14 KiB
C++
411 lines
No EOL
14 KiB
C++
///////////////////////////////////////////////////////////////////////////////
|
||
// 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
|
||
// Licensee’s 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.
|
||
//
|
||
///////////////////////////////////////////////////////////////////////////////
|
||
|
||
#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>
|
||
|
||
#include <OpenCVWrappers.h>
|
||
|
||
#include <LandmarkCoreIncludes.h>
|
||
|
||
#include <Face_utils.h>
|
||
#include <FaceAnalyser.h>
|
||
|
||
#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->sigma = 1.5;
|
||
params->reg_factor = 25;
|
||
params->weight_factor = 0;
|
||
}
|
||
|
||
// TODO adapt here as well
|
||
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>^>^ CalculateLandmarks() {
|
||
vector<cv::Point2d> vecLandmarks = ::LandmarkDetector::CalculateLandmarks(*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>^>^ CalculateEyeLandmarks() {
|
||
vector<cv::Point2d> vecLandmarks = ::LandmarkDetector::CalculateEyeLandmarks(*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 |