452 lines
15 KiB
C++
452 lines
15 KiB
C++
///////////////////////////////////////////////////////////////////////////////
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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 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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#include <sstream>
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#include <iomanip>
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#include <map>
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#include <set>
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#include "Visualizer.h"
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#include "VisualizationUtils.h"
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#include "RotationHelpers.h"
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#include "ImageManipulationHelpers.h"
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// For drawing on images
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#include <opencv2/imgproc.hpp>
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using namespace Utilities;
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// For subpixel accuracy drawing
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const int draw_shiftbits = 4;
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const int draw_multiplier = 1 << 4;
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const std::map<std::string, std::string> AUS_DESCRIPTION = {
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{"AU01", "Inner Brow Raiser "},
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{"AU02", "Outer Brow Raiser "},
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{"AU04", "Brow Lowerer "},
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{"AU05", "Upper Lid Raiser "},
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{"AU06", "Cheek Raiser "},
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{"AU07", "Lid Tightener "},
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{"AU09", "Nose Wrinkler "},
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{"AU10", "Upper Lip Raiser "},
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{"AU12", "Lip Corner Puller "},
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{"AU14", "Dimpler "},
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{"AU15", "Lip Corner Depressor"},
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{"AU17", "Chin Raiser "},
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{"AU20", "Lip stretcher "},
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{"AU23", "Lip Tightener "},
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{"AU25", "Lips part "},
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{"AU26", "Jaw Drop "},
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{"AU28", "Lip Suck "},
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{"AU45", "Blink "},
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};
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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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this->vis_aus = 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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vis_aus = 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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else if (arguments[i].compare("-vis-aus") == 0)
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{
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vis_aus = 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, bool vis_aus)
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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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this->vis_aus = vis_aus;
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}
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// Setting the image on which to draw
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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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// Convert the image to 8 bit RGB
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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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// Clearing other images
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hog_image = cv::Mat();
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aligned_face_image = cv::Mat();
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action_units_image = cv::Mat();
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}
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void Visualizer::SetObservationFaceAlign(const cv::Mat& aligned_face)
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{
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if(this->aligned_face_image.empty())
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{
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this->aligned_face_image = aligned_face;
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}
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else
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{
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cv::vconcat(this->aligned_face_image, aligned_face, this->aligned_face_image);
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}
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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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if(vis_hog)
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{
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if (this->hog_image.empty())
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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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else
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{
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cv::Mat tmp_hog;
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Visualise_FHOG(hog_descriptor, num_rows, num_cols, tmp_hog);
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cv::vconcat(this->hog_image, tmp_hog, this->hog_image);
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}
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}
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}
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void Visualizer::SetObservationLandmarks(const cv::Mat_<double>& landmarks_2D, double confidence, const cv::Mat_<int>& visibilities)
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{
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if(confidence > visualisation_boundary)
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{
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// Draw 2D landmarks on the image
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int n = landmarks_2D.rows / 2;
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// Drawing feature points
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for (int i = 0; i < n; ++i)
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{
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if (visibilities.empty() || visibilities.at<int>(i))
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{
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cv::Point featurePoint(cvRound(landmarks_2D.at<double>(i) * (double)draw_multiplier), cvRound(landmarks_2D.at<double>(i + n) * (double)draw_multiplier));
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// A rough heuristic for drawn point size
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int thickness = (int)std::ceil(3.0* ((double)captured_image.cols) / 640.0);
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int thickness_2 = (int)std::ceil(1.0* ((double)captured_image.cols) / 640.0);
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cv::circle(captured_image, featurePoint, 1 * draw_multiplier, cv::Scalar(0, 0, 255), thickness, CV_AA, draw_shiftbits);
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cv::circle(captured_image, featurePoint, 1 * draw_multiplier, cv::Scalar(255, 0, 0), thickness_2, CV_AA, draw_shiftbits);
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}
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else
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{
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// Draw a fainter point if the landmark is self occluded
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cv::Point featurePoint(cvRound(landmarks_2D.at<double>(i) * (double)draw_multiplier), cvRound(landmarks_2D.at<double>(i + n) * (double)draw_multiplier));
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// A rough heuristic for drawn point size
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int thickness = (int)std::ceil(2.5* ((double)captured_image.cols) / 640.0);
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int thickness_2 = (int)std::ceil(1.0* ((double)captured_image.cols) / 640.0);
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cv::circle(captured_image, featurePoint, 1 * draw_multiplier, cv::Scalar(0, 0, 155), thickness, CV_AA, draw_shiftbits);
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cv::circle(captured_image, featurePoint, 1 * draw_multiplier, cv::Scalar(155, 0, 0), thickness_2, CV_AA, draw_shiftbits);
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}
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}
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}
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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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// 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::SetObservationActionUnits(const std::vector<std::pair<std::string, double> >& au_intensities,
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const std::vector<std::pair<std::string, double> >& au_occurences)
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{
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if(au_intensities.size() > 0 || au_occurences.size() > 0)
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{
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std::set<std::string> au_names;
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std::map<std::string, bool> occurences_map;
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std::map<std::string, double> intensities_map;
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for (size_t idx = 0; idx < au_intensities.size(); idx++)
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{
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au_names.insert(au_intensities[idx].first);
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intensities_map[au_intensities[idx].first] = au_intensities[idx].second;
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}
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for (size_t idx = 0; idx < au_occurences.size(); idx++)
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{
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au_names.insert(au_occurences[idx].first);
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occurences_map[au_occurences[idx].first] = au_occurences[idx].second;
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}
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const int AU_TRACKBAR_LENGTH = 400;
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const int AU_TRACKBAR_HEIGHT = 10;
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const int MARGIN_X = 185;
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const int MARGIN_Y = 10;
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const int nb_aus = au_names.size();
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// Do not reinitialize
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if(action_units_image.empty())
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{
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action_units_image = cv::Mat(nb_aus * (AU_TRACKBAR_HEIGHT + 10) + MARGIN_Y * 2, AU_TRACKBAR_LENGTH + MARGIN_X, CV_8UC3, cv::Scalar(255,255,255));
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}
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else
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{
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action_units_image.setTo(255);
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}
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std::map<std::string, std::pair<bool, double>> aus;
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// first, prepare a mapping "AU name" -> { present, intensity }
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for (auto au_name : au_names)
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{
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// Insert the intensity and AU presense (as these do not always overlap check if they exist first)
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bool occurence = false;
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if (occurences_map.find(au_name) != occurences_map.end())
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{
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occurence = occurences_map[au_name] != 0;
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}
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else
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{
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// If we do not have an occurence label, trust the intensity one
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occurence = intensities_map[au_name] > 1;
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}
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double intensity = 0.0;
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if (intensities_map.find(au_name) != intensities_map.end())
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{
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intensity = intensities_map[au_name];
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}
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else
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{
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// If we do not have an intensity label, trust the occurence one
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intensity = occurences_map[au_name] == 0 ? 0 : 5;
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}
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aus[au_name] = std::make_pair(occurence, intensity);
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}
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// then, build the graph
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size_t idx = 0;
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for (auto& au : aus)
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{
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std::string name = au.first;
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bool present = au.second.first;
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double intensity = au.second.second;
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auto offset = MARGIN_Y + idx * (AU_TRACKBAR_HEIGHT + 10);
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std::ostringstream au_i;
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au_i << std::setprecision(2) << std::setw(4) << std::fixed << intensity;
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cv::putText(action_units_image, name, cv::Point(10, offset + 10), CV_FONT_HERSHEY_SIMPLEX, 0.5, CV_RGB(present ? 0 : 200, 0, 0), 1, CV_AA);
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cv::putText(action_units_image, AUS_DESCRIPTION.at(name), cv::Point(55, offset + 10), CV_FONT_HERSHEY_SIMPLEX, 0.3, CV_RGB(0, 0, 0), 1, CV_AA);
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if(present)
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{
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cv::putText(action_units_image, au_i.str(), cv::Point(160, offset + 10), CV_FONT_HERSHEY_SIMPLEX, 0.3, CV_RGB(0, 100, 0), 1, CV_AA);
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cv::rectangle(action_units_image, cv::Point(MARGIN_X, offset),
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cv::Point(MARGIN_X + AU_TRACKBAR_LENGTH * intensity/5, offset + AU_TRACKBAR_HEIGHT),
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cv::Scalar(128,128,128),
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CV_FILLED);
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}
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else
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{
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cv::putText(action_units_image, "0.00", cv::Point(160, offset + 10), CV_FONT_HERSHEY_SIMPLEX, 0.3, CV_RGB(0, 0, 0), 1, CV_AA);
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}
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idx++;
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}
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}
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}
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// Eye gaze infomration drawing, first of eye landmarks then of gaze
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void Visualizer::SetObservationGaze(const cv::Point3f& gaze_direction0, const cv::Point3f& gaze_direction1, const std::vector<cv::Point2d>& eye_landmarks2d, const std::vector<cv::Point3d>& eye_landmarks3d, double confidence)
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{
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if(confidence > visualisation_boundary)
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{
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if (eye_landmarks2d.size() > 0)
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{
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// First draw the eye region landmarks
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for (size_t i = 0; i < eye_landmarks2d.size(); ++i)
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{
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cv::Point featurePoint(cvRound(eye_landmarks2d[i].x * (double)draw_multiplier), cvRound(eye_landmarks2d[i].y * (double)draw_multiplier));
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// A rough heuristic for drawn point size
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int thickness = 1;
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int thickness_2 = 1;
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size_t next_point = i + 1;
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if (i == 7)
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next_point = 0;
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if (i == 19)
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next_point = 8;
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if (i == 27)
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next_point = 20;
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if (i == 7 + 28)
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next_point = 0 + 28;
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if (i == 19 + 28)
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next_point = 8 + 28;
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if (i == 27 + 28)
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next_point = 20 + 28;
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cv::Point nextFeaturePoint(cvRound(eye_landmarks2d[next_point].x * (double)draw_multiplier), cvRound(eye_landmarks2d[next_point].y * (double)draw_multiplier));
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if ((i < 28 && (i < 8 || i > 19)) || (i >= 28 && (i < 8 + 28 || i > 19 + 28)))
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cv::line(captured_image, featurePoint, nextFeaturePoint, cv::Scalar(255, 0, 0), thickness_2, CV_AA, draw_shiftbits);
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else
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cv::line(captured_image, featurePoint, nextFeaturePoint, cv::Scalar(0, 0, 255), thickness_2, CV_AA, draw_shiftbits);
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}
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// Now draw the gaze lines themselves
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cv::Mat cameraMat = (cv::Mat_<double>(3, 3) << fx, 0, cx, 0, fy, cy, 0, 0, 0);
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// Grabbing the pupil location, to draw eye gaze need to know where the pupil is
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cv::Point3d pupil_left(0, 0, 0);
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cv::Point3d pupil_right(0, 0, 0);
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for (size_t i = 0; i < 8; ++i)
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{
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pupil_left = pupil_left + eye_landmarks3d[i];
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pupil_right = pupil_right + eye_landmarks3d[i + eye_landmarks3d.size()/2];
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}
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pupil_left = pupil_left / 8;
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pupil_right = pupil_right / 8;
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std::vector<cv::Point3d> points_left;
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points_left.push_back(cv::Point3d(pupil_left));
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points_left.push_back(cv::Point3d(pupil_left + cv::Point3d(gaze_direction0)*50.0));
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std::vector<cv::Point3d> points_right;
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points_right.push_back(cv::Point3d(pupil_right));
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points_right.push_back(cv::Point3d(pupil_right + cv::Point3d(gaze_direction1)*50.0));
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cv::Mat_<double> proj_points;
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cv::Mat_<double> mesh_0 = (cv::Mat_<double>(2, 3) << points_left[0].x, points_left[0].y, points_left[0].z, points_left[1].x, points_left[1].y, points_left[1].z);
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Project(proj_points, mesh_0, fx, fy, cx, cy);
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cv::line(captured_image, cv::Point(cvRound(proj_points.at<double>(0, 0) * (double)draw_multiplier), cvRound(proj_points.at<double>(0, 1) * (double)draw_multiplier)),
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cv::Point(cvRound(proj_points.at<double>(1, 0) * (double)draw_multiplier), cvRound(proj_points.at<double>(1, 1) * (double)draw_multiplier)), cv::Scalar(110, 220, 0), 2, CV_AA, draw_shiftbits);
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cv::Mat_<double> mesh_1 = (cv::Mat_<double>(2, 3) << points_right[0].x, points_right[0].y, points_right[0].z, points_right[1].x, points_right[1].y, points_right[1].z);
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Project(proj_points, mesh_1, fx, fy, cx, cy);
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cv::line(captured_image, cv::Point(cvRound(proj_points.at<double>(0, 0) * (double)draw_multiplier), cvRound(proj_points.at<double>(0, 1) * (double)draw_multiplier)),
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cv::Point(cvRound(proj_points.at<double>(1, 0) * (double)draw_multiplier), cvRound(proj_points.at<double>(1, 1) * (double)draw_multiplier)), cv::Scalar(110, 220, 0), 2, CV_AA, draw_shiftbits);
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}
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}
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}
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void Visualizer::SetFps(double fps)
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{
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// Write out the framerate on the image before displaying it
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char fpsC[255];
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std::sprintf(fpsC, "%d", (int)fps);
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std::string fpsSt("FPS:");
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fpsSt += fpsC;
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cv::putText(captured_image, fpsSt, cv::Point(10, 20), CV_FONT_HERSHEY_SIMPLEX, 0.5, CV_RGB(255, 0, 0), 1, CV_AA);
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}
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char Visualizer::ShowObservation()
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{
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if (vis_align)
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{
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cv::imshow("sim_warp", aligned_face_image);
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}
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if (vis_hog)
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{
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cv::imshow("hog", hog_image);
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}
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if (vis_aus && !action_units_image.empty())
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{
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cv::imshow("action units", action_units_image);
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}
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if (vis_track)
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{
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cv::imshow("tracking result", captured_image);
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}
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return cv::waitKey(1);
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}
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cv::Mat Visualizer::GetVisImage()
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{
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return captured_image;
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}
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cv::Mat Visualizer::GetHOGVis()
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{
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return hog_image;
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}
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