0a5110a003
Conflicts: .gitignore matlab_runners/Action Unit Experiments/DISFA_valid_res.txt matlab_runners/Feature Point Experiments/results/fps_yt.mat matlab_runners/Feature Point Experiments/results/in-the-wild-res-no-outline.pdf matlab_runners/Feature Point Experiments/results/landmark_detections.mat matlab_runners/Gaze Experiments/mpii_1500_errs.mat matlab_runners/Gaze Experiments/mpii_1500_errs.txt matlab_runners/Head Pose Experiments/results/Pose_OF.mat
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14 KiB
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395 lines
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14 KiB
C++
///////////////////////////////////////////////////////////////////////////////
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// Copyright (C) 2016, Carnegie Mellon University and University of Cambridge,
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// all rights reserved.
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//
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// THIS SOFTWARE IS PROVIDED “AS IS” FOR ACADEMIC USE ONLY AND ANY EXPRESS
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// OR IMPLIED WARRANTIES WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
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// THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS
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// BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY.
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// OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
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// HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
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// STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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// ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Notwithstanding the license granted herein, Licensee acknowledges that certain components
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// of the Software may be covered by so-called “open source” software licenses (“Open Source
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// Components”), which means any software licenses approved as open source licenses by the
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// Open Source Initiative or any substantially similar licenses, including without limitation any
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// license that, as a condition of distribution of the software licensed under such license,
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// requires that the distributor make the software available in source code format. Licensor shall
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// provide a list of Open Source Components for a particular version of the Software upon
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// Licensee’s request. Licensee will comply with the applicable terms of such licenses and to
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// the extent required by the licenses covering Open Source Components, the terms of such
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// licenses will apply in lieu of the terms of this Agreement. To the extent the terms of the
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// licenses applicable to Open Source Components prohibit any of the restrictions in this
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// License Agreement with respect to such Open Source Component, such restrictions will not
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// apply to such Open Source Component. To the extent the terms of the licenses applicable to
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// Open Source Components require Licensor to make an offer to provide source code or
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// related information in connection with the Software, such offer is hereby made. Any request
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// for source code or related information should be directed to cl-face-tracker-distribution@lists.cam.ac.uk
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// Licensee acknowledges receipt of notices for the Open Source Components for the initial
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// delivery of the Software.
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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: an open source facial behavior analysis toolkit
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// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency
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// in IEEE Winter Conference on Applications of Computer Vision, 2016
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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-speci?c 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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// Constrained Local Neural Fields for robust facial landmark detection in the wild.
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// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency.
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// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
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//
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///////////////////////////////////////////////////////////////////////////////
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#ifndef __LANDMARK_DETECTOR_INTEROP_h_
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#define __LANDMARK_DETECTOR_INTEROP_h_
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#pragma once
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#pragma managed
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#include <msclr\marshal.h>
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#include <msclr\marshal_cppstd.h>
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#pragma unmanaged
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// Include all the unmanaged things we need.
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#include <opencv2/core/core.hpp>
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#include "opencv2/objdetect.hpp"
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#include "opencv2/calib3d.hpp"
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#include <opencv2/imgcodecs.hpp>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/highgui/highgui.hpp>
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#include <OpenCVWrappers.h>
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#include <LandmarkCoreIncludes.h>
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#include <Face_utils.h>
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#include <FaceAnalyser.h>
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#pragma managed
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namespace CppInterop {
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namespace LandmarkDetector {
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public ref class FaceModelParameters
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{
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public:
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::LandmarkDetector::FaceModelParameters* params;
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public:
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// Initialise the parameters
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FaceModelParameters(System::String^ root)
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{
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std::string root_std = msclr::interop::marshal_as<std::string>(root);
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vector<std::string> args;
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args.push_back(root_std);
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params = new ::LandmarkDetector::FaceModelParameters(args);
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params->track_gaze = true;
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}
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// TODO this could have optimize for demo mode (also could appropriately update sigma, reg_factor as well)
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void optimiseForVideo()
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{
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params->window_sizes_small = vector<int>(4);
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params->window_sizes_init = vector<int>(4);
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// For fast tracking
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params->window_sizes_small[0] = 0;
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params->window_sizes_small[1] = 9;
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params->window_sizes_small[2] = 7;
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params->window_sizes_small[3] = 5;
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// Just for initialisation
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params->window_sizes_init.at(0) = 11;
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params->window_sizes_init.at(1) = 9;
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params->window_sizes_init.at(2) = 7;
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params->window_sizes_init.at(3) = 5;
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// For first frame use the initialisation
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params->window_sizes_current = params->window_sizes_init;
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params->sigma = 1.5;
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params->reg_factor = 25;
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params->weight_factor = 0;
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}
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// TODO adapt here as well
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void optimiseForImages()
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{
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params->window_sizes_init = vector<int>(4);
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params->window_sizes_init[0] = 15;
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params->window_sizes_init[1] = 13;
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params->window_sizes_init[2] = 11;
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params->window_sizes_init[3] = 9;
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params->multi_view = true;
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params->sigma = 1.25;
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params->reg_factor = 35;
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params->weight_factor = 2.5;
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params->num_optimisation_iteration = 10;
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}
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::LandmarkDetector::FaceModelParameters* getParams() {
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return params;
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}
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~FaceModelParameters()
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{
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delete params;
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}
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};
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public ref class CLNF
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{
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public:
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// A pointer to the CLNF landmark detector
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::LandmarkDetector::CLNF* clnf;
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public:
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// Wrapper functions for the relevant CLNF functionality
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CLNF() : clnf(new ::LandmarkDetector::CLNF()) { }
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CLNF(FaceModelParameters^ params)
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{
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clnf = new ::LandmarkDetector::CLNF(params->getParams()->model_location);
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}
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~CLNF()
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{
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delete clnf;
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}
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::LandmarkDetector::CLNF* getCLM() {
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return clnf;
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}
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void Reset() {
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clnf->Reset();
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}
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void Reset(double x, double y) {
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clnf->Reset(x, y);
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}
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double GetConfidence()
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{
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return clnf->detection_certainty;
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}
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bool DetectLandmarksInVideo(OpenCVWrappers::RawImage^ image, FaceModelParameters^ clmParams) {
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return ::LandmarkDetector::DetectLandmarksInVideo(image->Mat, *clnf, *clmParams->getParams());
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}
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bool DetectFaceLandmarksInImage(OpenCVWrappers::RawImage^ image, FaceModelParameters^ clmParams) {
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return ::LandmarkDetector::DetectLandmarksInImage(image->Mat, *clnf, *clmParams->getParams());
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}
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System::Collections::Generic::List<System::Collections::Generic::List<System::Tuple<double,double>^>^>^ DetectMultiFaceLandmarksInImage(OpenCVWrappers::RawImage^ image, FaceModelParameters^ clmParams) {
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auto all_landmarks = gcnew System::Collections::Generic::List<System::Collections::Generic::List<System::Tuple<double,double>^>^>();
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// Detect faces in an image
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vector<cv::Rect_<double> > face_detections;
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vector<double> confidences;
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// TODO this should be pre-allocated as now it might be a bit too slow
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dlib::frontal_face_detector face_detector_hog = dlib::get_frontal_face_detector();
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::LandmarkDetector::DetectFacesHOG(face_detections, image->Mat, face_detector_hog, confidences);
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// Detect landmarks around detected faces
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int face_det = 0;
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// perform landmark detection for every face detected
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for(size_t face=0; face < face_detections.size(); ++face)
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{
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cv::Mat depth;
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// if there are multiple detections go through them
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bool success = ::LandmarkDetector::DetectLandmarksInImage(image->Mat, depth, face_detections[face], *clnf, *clmParams->getParams());
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auto landmarks_curr = gcnew System::Collections::Generic::List<System::Tuple<double,double>^>();
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if(clnf->detected_landmarks.cols == 1)
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{
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int n = clnf->detected_landmarks.rows / 2;
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for(int i = 0; i < n; ++i)
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{
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landmarks_curr->Add(gcnew System::Tuple<double,double>(clnf->detected_landmarks.at<double>(i,0), clnf->detected_landmarks.at<double>(i+n,0)));
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}
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}
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else
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{
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int n = clnf->detected_landmarks.cols / 2;
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for(int i = 0; i < clnf->detected_landmarks.cols; ++i)
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{
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landmarks_curr->Add(gcnew System::Tuple<double,double>(clnf->detected_landmarks.at<double>(0,i), clnf->detected_landmarks.at<double>(0,i+1)));
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}
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}
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all_landmarks->Add(landmarks_curr);
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}
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return all_landmarks;
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}
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void GetCorrectedPoseCamera(System::Collections::Generic::List<double>^ pose, double fx, double fy, double cx, double cy) {
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auto pose_vec = ::LandmarkDetector::GetCorrectedPoseCamera(*clnf, fx, fy, cx, cy);
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pose->Clear();
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for(int i = 0; i < 6; ++i)
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{
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pose->Add(pose_vec[i]);
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}
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}
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void GetCorrectedPoseWorld(System::Collections::Generic::List<double>^ pose, double fx, double fy, double cx, double cy) {
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auto pose_vec = ::LandmarkDetector::GetCorrectedPoseWorld(*clnf, fx, fy, cx, cy);
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pose->Clear();
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for(int i = 0; i < 6; ++i)
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{
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pose->Add(pose_vec[i]);
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}
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}
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System::Collections::Generic::List<System::Tuple<double,double>^>^ CalculateLandmarks() {
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vector<cv::Point2d> vecLandmarks = ::LandmarkDetector::CalculateLandmarks(*clnf);
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auto landmarks = gcnew System::Collections::Generic::List<System::Tuple<double,double>^>();
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for(cv::Point2d p : vecLandmarks) {
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landmarks->Add(gcnew System::Tuple<double,double>(p.x, p.y));
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}
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return landmarks;
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}
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System::Collections::Generic::List<System::Windows::Media::Media3D::Point3D>^ Calculate3DLandmarks(double fx, double fy, double cx, double cy) {
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cv::Mat_<double> shape3D = clnf->GetShape(fx, fy, cx, cy);
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auto landmarks_3D = gcnew System::Collections::Generic::List<System::Windows::Media::Media3D::Point3D>();
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for(int i = 0; i < shape3D.cols; ++i)
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{
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landmarks_3D->Add(System::Windows::Media::Media3D::Point3D(shape3D.at<double>(0, i), shape3D.at<double>(1, i), shape3D.at<double>(2, i)));
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}
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return landmarks_3D;
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}
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// Static functions from the CLMTracker namespace.
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void DrawLandmarks(OpenCVWrappers::RawImage^ img, System::Collections::Generic::List<System::Windows::Point>^ landmarks) {
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vector<cv::Point> vecLandmarks;
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for(int i = 0; i < landmarks->Count; i++) {
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System::Windows::Point p = landmarks[i];
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vecLandmarks.push_back(cv::Point(p.X, p.Y));
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}
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::LandmarkDetector::DrawLandmarks(img->Mat, vecLandmarks);
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}
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System::Collections::Generic::List<System::Tuple<System::Windows::Point, System::Windows::Point>^>^ CalculateBox(float fx, float fy, float cx, float cy) {
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cv::Vec6d pose = ::LandmarkDetector::GetCorrectedPoseWorld(*clnf, fx,fy, cx, cy);
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vector<pair<cv::Point2d, cv::Point2d>> vecLines = ::LandmarkDetector::CalculateBox(pose, fx, fy, cx, cy);
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auto lines = gcnew System::Collections::Generic::List<System::Tuple<System::Windows::Point,System::Windows::Point>^>();
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for(pair<cv::Point2d, cv::Point2d> line : vecLines) {
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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)));
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}
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return lines;
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}
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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) {
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cv::Scalar color = cv::Scalar(r,g,b,1);
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vector<pair<cv::Point, cv::Point>> vecLines;
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for(int i = 0; i < lines->Count; i++) {
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System::Tuple<System::Windows::Point, System::Windows::Point>^ points = lines[i];
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vecLines.push_back(pair<cv::Point, cv::Point>(cv::Point(points->Item1.X, points->Item1.Y), cv::Point(points->Item2.X, points->Item2.Y)));
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}
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::LandmarkDetector::DrawBox(vecLines, image->Mat, color, thickness);
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}
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int GetNumPoints()
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{
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return clnf->pdm.NumberOfPoints();
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}
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int GetNumModes()
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{
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return clnf->pdm.NumberOfModes();
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}
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// Getting the non-rigid shape parameters describing the facial expression
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System::Collections::Generic::List<double>^ GetNonRigidParams()
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{
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auto non_rigid_params = gcnew System::Collections::Generic::List<double>();
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for (int i = 0; i < clnf->params_local.rows; ++i)
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{
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non_rigid_params->Add(clnf->params_local.at<double>(i));
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}
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return non_rigid_params;
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}
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// Getting the rigid shape parameters describing face scale rotation and translation (scale,rotx,roty,rotz,tx,ty)
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System::Collections::Generic::List<double>^ GetRigidParams()
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{
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auto rigid_params = gcnew System::Collections::Generic::List<double>();
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for (size_t i = 0; i < 6; ++i)
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{
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rigid_params->Add(clnf->params_global[i]);
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}
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return rigid_params;
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}
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// Rigid params followed by non-rigid ones
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System::Collections::Generic::List<double>^ GetParams()
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{
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auto all_params = GetRigidParams();
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all_params->AddRange(GetNonRigidParams());
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return all_params;
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}
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};
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}
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}
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#endif |