141 lines
4.5 KiB
C++
141 lines
4.5 KiB
C++
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///////////////////////////////////////////////////////////////////////////////
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// Copyright (C) 2017, Tadas Baltrusaitis, all rights reserved.
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//
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// ACADEMIC OR NON-PROFIT ORGANIZATION NONCOMMERCIAL RESEARCH USE ONLY
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//
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// BY USING OR DOWNLOADING THE SOFTWARE, YOU ARE AGREEING TO THE TERMS OF THIS LICENSE AGREEMENT.
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// IF YOU DO NOT AGREE WITH THESE TERMS, YOU MAY NOT USE OR DOWNLOAD THE SOFTWARE.
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//
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// License can be found in OpenFace-license.txt
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//
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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 Baltru<72>aitis, 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 Baltru<72>aitis, 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 Baltru<72>aitis, 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 Baltru<72>aitis, 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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#include "Visualizer.h"
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#include "VisualizationUtils.h"
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using namespace Utilities;
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Visualizer::Visualizer(std::vector<std::string> arguments)
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{
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// By default not visualizing anything
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this->vis_track = false;
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this->vis_hog = false;
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this->vis_align = false;
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for (size_t i = 0; i < arguments.size(); ++i)
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{
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if (arguments[i].compare("-verbose") == 0)
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{
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vis_track = true;
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vis_align = true;
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vis_hog = true;
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}
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else if (arguments[i].compare("-vis-align") == 0)
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{
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vis_align = true;
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}
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else if (arguments[i].compare("-vis-hog") == 0)
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{
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vis_hog = true;
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}
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else if (arguments[i].compare("-vis-track") == 0)
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{
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vis_track = true;
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}
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}
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}
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Visualizer::Visualizer(bool vis_track, bool vis_hog, bool vis_align)
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{
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this->vis_track = vis_track;
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this->vis_hog = vis_hog;
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this->vis_align = vis_align;
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}
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void Visualizer::SetImage(const cv::Mat& canvas, float fx, float fy, float cx, float cy)
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{
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captured_image = canvas.clone();
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this->fx = fx;
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this->fy = fy;
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this->cx = cx;
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this->cy = cy;
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}
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void Visualizer::SetObservationFaceAlign(const cv::Mat& aligned_face)
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{
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this->aligned_face_image = aligned_face;
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}
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void Visualizer::SetObservationHOG(const cv::Mat_<double>& hog_descriptor, int num_cols, int num_rows)
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{
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Visualise_FHOG(hog_descriptor, num_rows, num_cols, this->hog_image);
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}
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void Visualizer::SetObservationLandmarks(const cv::Mat_<double>& landmarks_2D, double confidence, bool success, const cv::Mat_<int>& visibilities)
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{
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DrawLandmarkDetResults(captured_image, landmarks_2D, visibilities);
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}
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void Visualizer::SetObservationPose(const cv::Vec6d& pose, double confidence)
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{
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double visualisation_boundary = 0.4;
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// Only draw if the reliability is reasonable, the value is slightly ad-hoc
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if (confidence > visualisation_boundary)
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{
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double vis_certainty = confidence;
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if (vis_certainty > 1)
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vis_certainty = 1;
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// Scale from 0 to 1, to allow to indicated by colour how confident we are in the tracking
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vis_certainty = (vis_certainty - visualisation_boundary) / (1 - visualisation_boundary);
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// A rough heuristic for box around the face width
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int thickness = (int)std::ceil(2.0* ((double)captured_image.cols) / 640.0);
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// Draw it in reddish if uncertain, blueish if certain
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DrawBox(captured_image, pose, cv::Scalar(vis_certainty*255.0, 0, (1 - vis_certainty) * 255), thickness, fx, fy, cx, cy);
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}
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}
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void Visualizer::SetObservationGaze(const cv::Point3f& gaze_direction0, const cv::Point3f& gaze_direction1,
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const cv::Vec2d& gaze_angle, const std::vector<cv::Point2d>& eye_landmarks)
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{
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// TODO actual drawing
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if (det_parameters.track_gaze && detection_success && face_model.eye_model)
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{
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GazeAnalysis::DrawGaze(captured_image, face_model, gazeDirection0, gazeDirection1, fx, fy, cx, cy);
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}
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}
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