498 lines
No EOL
16 KiB
C++
498 lines
No EOL
16 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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// FaceAnalyser_Interop.h
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#ifndef __FACE_ANALYSER_INTEROP_h_
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#define __FACE_ANALYSER_INTEROP_h_
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#pragma once
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// Include all the unmanaged things we need.
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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 <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 <LandmarkDetectorInterop.h>
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#include <Face_utils.h>
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#include <FaceAnalyser.h>
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#include <GazeEstimation.h>
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// Allows to overcome boost name clash stuff with C++ CLI
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#ifdef __cplusplus_cli
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#define generic __identifier(generic)
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#endif
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// Boost stuff
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#include <filesystem.hpp>
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#include <filesystem/fstream.hpp>
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#ifdef __cplusplus_cli
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#undef generic
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#endif
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#pragma managed
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namespace FaceAnalyser_Interop {
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public ref class FaceAnalyserManaged
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{
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private:
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FaceAnalysis::FaceAnalyser* face_analyser;
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// The actual descriptors (for visualisation and output)
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cv::Mat_<double>* hog_features;
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cv::Mat* aligned_face;
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cv::Mat* visualisation;
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cv::Mat* tracked_face;
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// Variables used for recording things
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std::ofstream* hog_output_file;
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std::string* align_output_dir;
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int* num_rows;
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int* num_cols;
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bool* good_frame;
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cv::VideoWriter* tracked_vid_writer;
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// Variable storing gaze for recording
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// Absolute gaze direction
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cv::Point3f* gazeDirection0;
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cv::Point3f* gazeDirection1;
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cv::Vec2d* gazeAngle;
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cv::Point3f* pupil_left;
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cv::Point3f* pupil_right;
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public:
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FaceAnalyserManaged(System::String^ root, bool dynamic, int output_width)
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{
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vector<cv::Vec3d> orientation_bins;
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orientation_bins.push_back(cv::Vec3d(0,0,0));
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int width = output_width;
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int height = output_width;
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double scale = width * (0.7 / 112.0);
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string root_std = msclr::interop::marshal_as<std::string>(root);
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// TODO diff paths and locations for the demo mode
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boost::filesystem::path tri_loc = boost::filesystem::path(root_std) / "model" / "tris_68_full.txt";
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boost::filesystem::path au_loc;
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if(dynamic)
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{
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au_loc = boost::filesystem::path(root_std) / "AU_predictors" / "AU_all_best.txt";
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}
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else
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{
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au_loc = boost::filesystem::path(root_std) / "AU_predictors" / "AU_all_static.txt";
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}
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face_analyser = new FaceAnalysis::FaceAnalyser(orientation_bins, scale, width, height, au_loc.string(), tri_loc.string());
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hog_features = new cv::Mat_<double>();
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aligned_face = new cv::Mat();
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visualisation = new cv::Mat();
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tracked_face = new cv::Mat();
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num_rows = new int;
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num_cols = new int;
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good_frame = new bool;
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align_output_dir = new string();
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hog_output_file = new std::ofstream();
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gazeDirection0 = new cv::Point3f();
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gazeDirection1 = new cv::Point3f();
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gazeAngle = new cv::Vec2d();
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pupil_left = new cv::Point3f();
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pupil_right = new cv::Point3f();
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}
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void SetupAlignedImageRecording(System::String^ directory)
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{
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*align_output_dir = msclr::interop::marshal_as<std::string>(directory);
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}
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void SetupHOGRecording(System::String^ file)
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{
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// Create the file for recording
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hog_output_file->open(msclr::interop::marshal_as<std::string>(file), ios_base::out | ios_base::binary);
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}
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void SetupTrackingRecording(System::String^ file, int width, int height, double fps)
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{
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tracked_vid_writer = new cv::VideoWriter(msclr::interop::marshal_as<std::string>(file), CV_FOURCC('D', 'I', 'V', 'X'), fps, cv::Size(width, height));
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}
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void StopHOGRecording()
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{
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hog_output_file->close();
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}
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void StopTrackingRecording()
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{
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tracked_vid_writer->release();
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}
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void RecordAlignedFrame(int frame_num)
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{
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char name[100];
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// output the frame number
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sprintf(name, "frame_det_%06d.bmp", frame_num);
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string out_file = (boost::filesystem::path(*align_output_dir) / boost::filesystem::path(name)).string();
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imwrite(out_file, *aligned_face);
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}
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void RecordHOGFrame()
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{
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// Using FHOGs, hence 31 channels
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int num_channels = 31;
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hog_output_file->write((char*)(num_cols), 4);
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hog_output_file->write((char*)(num_rows), 4);
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hog_output_file->write((char*)(&num_channels), 4);
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// Not the best way to store a bool, but will be much easier to read it
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float good_frame_float;
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if(good_frame)
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good_frame_float = 1;
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else
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good_frame_float = -1;
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hog_output_file->write((char*)(&good_frame_float), 4);
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cv::MatConstIterator_<double> descriptor_it = hog_features->begin();
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for(int y = 0; y < *num_cols; ++y)
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{
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for(int x = 0; x < *num_rows; ++x)
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{
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for(unsigned int o = 0; o < 31; ++o)
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{
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float hog_data = (float)(*descriptor_it++);
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hog_output_file->write((char*)&hog_data, 4);
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}
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}
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}
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}
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void RecordTrackedFace()
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{
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tracked_vid_writer->write(*tracked_face);
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}
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void PostProcessOutputFile(System::String^ file, bool dynamic)
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{
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face_analyser->PostprocessOutputFile(msclr::interop::marshal_as<std::string>(file), dynamic);
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}
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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) {
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face_analyser->AddNextFrame(frame->Mat, *clnf->getCLNF(), 0, online, vis_hog);
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face_analyser->GetLatestHOG(*hog_features, *num_rows, *num_cols);
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face_analyser->GetLatestAlignedFace(*aligned_face);
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*good_frame = clnf->clnf->detection_success;
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if(vis_hog)
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{
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*visualisation = face_analyser->GetLatestHOGDescriptorVisualisation();
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}
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if(vis_tracked)
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{
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if(frame->Mat.cols != tracked_face->cols && frame->Mat.rows != tracked_face->rows)
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{
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*tracked_face = frame->Mat.clone();
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}
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else
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{
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frame->Mat.clone().copyTo(*tracked_face);
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}
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if(clnf->clnf->detection_success)
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{
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::LandmarkDetector::Draw(*tracked_face, *clnf->clnf);
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}
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tracked_face->deallocate();
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}
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// After the AUs have been detected do some gaze estimation as well
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FaceAnalysis::EstimateGaze(*clnf->getCLNF(), *gazeDirection0, fx, fy, cx, cy, true);
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FaceAnalysis::EstimateGaze(*clnf->getCLNF(), *gazeDirection1, fx, fy, cx, cy, false);
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// Estimate the gaze angle WRT to head pose here
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System::Collections::Generic::List<double>^ pose_list = gcnew System::Collections::Generic::List<double>();
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clnf->GetPose(pose_list, fx, fy, cx, cy);
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cv::Vec6d pose(pose_list[0], pose_list[1], pose_list[2], pose_list[3], pose_list[4], pose_list[5]);
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*gazeAngle = FaceAnalysis::GetGazeAngle(*gazeDirection0, *gazeDirection1, pose);
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// Grab pupil locations
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int part_left = -1;
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int part_right = -1;
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for (size_t i = 0; i < clnf->getCLNF()->hierarchical_models.size(); ++i)
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{
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if (clnf->getCLNF()->hierarchical_model_names[i].compare("left_eye_28") == 0)
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{
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part_left = i;
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}
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if (clnf->getCLNF()->hierarchical_model_names[i].compare("right_eye_28") == 0)
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{
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part_right = i;
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}
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}
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cv::Mat_<double> eyeLdmks3d_left = clnf->getCLNF()->hierarchical_models[part_left].GetShape(fx, fy, cx, cy);
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cv::Point3f pupil_left_h = FaceAnalysis::GetPupilPosition(eyeLdmks3d_left);
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pupil_left->x = pupil_left_h.x; pupil_left->y = pupil_left_h.y; pupil_left->z = pupil_left_h.z;
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cv::Mat_<double> eyeLdmks3d_right = clnf->getCLNF()->hierarchical_models[part_right].GetShape(fx, fy, cx, cy);
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cv::Point3f pupil_right_h = FaceAnalysis::GetPupilPosition(eyeLdmks3d_right);
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pupil_right->x = pupil_right_h.x; pupil_right->y = pupil_right_h.y; pupil_right->z = pupil_right_h.z;
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}
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System::Tuple<System::Tuple<double, double, double>^, System::Tuple<double, double, double>^>^ GetGazeCamera()
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{
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auto gaze0 = gcnew System::Tuple<double, double, double>(gazeDirection0->x, gazeDirection0->y, gazeDirection0->z);
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auto gaze1 = gcnew System::Tuple<double, double, double>(gazeDirection1->x, gazeDirection1->y, gazeDirection1->z);
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return gcnew System::Tuple<System::Tuple<double, double, double>^, System::Tuple<double, double, double>^>(gaze0, gaze1);
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}
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System::Tuple<double, double>^ GetGazeAngle()
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{
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auto gaze_angle = gcnew System::Tuple<double, double>((*gazeAngle)[0], (*gazeAngle)[1]);
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return gaze_angle;
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}
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System::Collections::Generic::List<System::Tuple<System::Windows::Point, System::Windows::Point>^>^ CalculateGazeLines(double scale, float fx, float fy, float cx, float cy)
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{
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cv::Mat_<double> cameraMat = (cv::Mat_<double>(3, 3) << fx, 0, cx, 0, fy, cy, 0, 0, 0);
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vector<cv::Point3f> points_left;
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points_left.push_back(cv::Point3f(*pupil_left));
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points_left.push_back(cv::Point3f(*pupil_left + *gazeDirection0 * 40.0 * scale));
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vector<cv::Point3f> points_right;
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points_right.push_back(cv::Point3f(*pupil_right));
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points_right.push_back(cv::Point3f(*pupil_right + *gazeDirection1 * 40.0 * scale));
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// Perform manual projection of points
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vector<cv::Point2d> imagePoints_left;
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for (int i = 0; i < points_left.size(); ++i)
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{
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double x = points_left[i].x * fx / points_left[i].z + cx;
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double y = points_left[i].y * fy / points_left[i].z + cy;
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imagePoints_left.push_back(cv::Point2d(x, y));
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}
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vector<cv::Point2d> imagePoints_right;
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for (int i = 0; i < points_right.size(); ++i)
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{
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double x = points_right[i].x * fx / points_right[i].z + cx;
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double y = points_right[i].y * fy / points_right[i].z + cy;
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imagePoints_right.push_back(cv::Point2d(x, y));
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}
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auto lines = gcnew System::Collections::Generic::List<System::Tuple<System::Windows::Point, System::Windows::Point>^>();
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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)));
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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)));
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return lines;
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}
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System::Collections::Generic::List<System::String^>^ GetClassActionUnitsNames()
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{
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auto names = face_analyser->GetAUClassNames();
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auto names_ret = gcnew System::Collections::Generic::List<System::String^>();
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for(std::string name : names)
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{
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names_ret->Add(gcnew System::String(name.c_str()));
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}
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return names_ret;
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}
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System::Collections::Generic::List<System::String^>^ GetRegActionUnitsNames()
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{
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auto names = face_analyser->GetAURegNames();
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auto names_ret = gcnew System::Collections::Generic::List<System::String^>();
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for(std::string name : names)
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{
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names_ret->Add(gcnew System::String(name.c_str()));
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}
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return names_ret;
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}
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System::Collections::Generic::Dictionary<System::String^, double>^ GetCurrentAUsClass()
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{
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auto classes = face_analyser->GetCurrentAUsClass();
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auto au_classes = gcnew System::Collections::Generic::Dictionary<System::String^, double>();
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for(auto p: classes)
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{
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au_classes->Add(gcnew System::String(p.first.c_str()), p.second);
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}
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return au_classes;
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}
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System::Collections::Generic::Dictionary<System::String^, double>^ GetCurrentAUsReg()
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{
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auto preds = face_analyser->GetCurrentAUsReg();
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auto au_preds = gcnew System::Collections::Generic::Dictionary<System::String^, double>();
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for(auto p: preds)
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{
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au_preds->Add(gcnew System::String(p.first.c_str()), p.second);
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}
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return au_preds;
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}
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OpenCVWrappers::RawImage^ GetLatestAlignedFace() {
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OpenCVWrappers::RawImage^ face_aligned_image = gcnew OpenCVWrappers::RawImage(*aligned_face);
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return face_aligned_image;
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}
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OpenCVWrappers::RawImage^ GetLatestHOGDescriptorVisualisation() {
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OpenCVWrappers::RawImage^ HOG_vis_image = gcnew OpenCVWrappers::RawImage(*visualisation);
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return HOG_vis_image;
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}
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void Reset()
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{
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face_analyser->Reset();
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}
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// Finalizer. Definitely called before Garbage Collection,
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// but not automatically called on explicit Dispose().
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// May be called multiple times.
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!FaceAnalyserManaged()
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{
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delete hog_features;
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delete aligned_face;
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delete visualisation;
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delete num_cols;
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delete num_rows;
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delete hog_output_file;
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delete good_frame;
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delete align_output_dir;
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delete face_analyser;
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delete tracked_face;
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||
|
||
delete gazeDirection0;
|
||
delete gazeDirection1;
|
||
delete gazeAngle;
|
||
|
||
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 |