196 lines
6.7 KiB
C++
196 lines
6.7 KiB
C++
///////////////////////////////////////////////////////////////////////////////
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// Copyright (C) 2017, Carnegie Mellon University and University of Cambridge,
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// 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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// * 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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// FaceTrackingVid.cpp : Defines the entry point for the console application for tracking faces in videos.
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// Libraries for landmark detection (includes CLNF and CLM modules)
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#include "LandmarkCoreIncludes.h"
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#include "GazeEstimation.h"
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#include <fstream>
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#include <sstream>
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// OpenCV includes
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#include <opencv2/videoio/videoio.hpp> // Video write
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#include <opencv2/videoio/videoio_c.h> // Video write
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#include <opencv2/imgproc.hpp>
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#include <opencv2/highgui/highgui.hpp>
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#include <SequenceCapture.h>
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#include <Visualizer.h>
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#include <VisualizationUtils.h>
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// Boost includes
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#include <filesystem.hpp>
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#include <filesystem/fstream.hpp>
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#define INFO_STREAM( stream ) \
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std::cout << stream << std::endl
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#define WARN_STREAM( stream ) \
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std::cout << "Warning: " << stream << std::endl
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#define ERROR_STREAM( stream ) \
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std::cout << "Error: " << stream << std::endl
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static void printErrorAndAbort( const std::string & error )
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{
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std::cout << error << std::endl;
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abort();
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}
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#define FATAL_STREAM( stream ) \
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printErrorAndAbort( std::string( "Fatal error: " ) + stream )
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using namespace std;
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vector<string> get_arguments(int argc, char **argv)
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{
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vector<string> arguments;
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for(int i = 0; i < argc; ++i)
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{
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arguments.push_back(string(argv[i]));
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}
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return arguments;
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}
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int main (int argc, char **argv)
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{
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vector<string> arguments = get_arguments(argc, argv);
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// no arguments: output usage
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if (arguments.size() == 1)
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{
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cout << "For command line arguments see:" << endl;
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cout << " https://github.com/TadasBaltrusaitis/OpenFace/wiki/Command-line-arguments";
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return 0;
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}
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LandmarkDetector::FaceModelParameters det_parameters(arguments);
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// The modules that are being used for tracking
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LandmarkDetector::CLNF face_model(det_parameters.model_location);
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if (!face_model.eye_model)
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{
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cout << "WARNING: no eye model found" << endl;
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}
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// Open a sequence
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Utilities::SequenceCapture sequence_reader;
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// A utility for visualizing the results (show just the tracks)
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Utilities::Visualizer visualizer(true, false, false, false);
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// Tracking FPS for visualization
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Utilities::FpsTracker fps_tracker;
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fps_tracker.AddFrame();
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int sequence_number = 0;
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while (true) // this is not a for loop as we might also be reading from a webcam
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{
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// The sequence reader chooses what to open based on command line arguments provided
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if (!sequence_reader.Open(arguments))
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break;
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INFO_STREAM("Device or file opened");
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cv::Mat captured_image = sequence_reader.GetNextFrame();
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INFO_STREAM("Starting tracking");
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while (!captured_image.empty()) // this is not a for loop as we might also be reading from a webcam
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{
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// Reading the images
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cv::Mat_<uchar> grayscale_image = sequence_reader.GetGrayFrame();
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// The actual facial landmark detection / tracking
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bool detection_success = LandmarkDetector::DetectLandmarksInVideo(grayscale_image, face_model, det_parameters);
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// Gaze tracking, absolute gaze direction
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cv::Point3f gazeDirection0(0, 0, -1);
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cv::Point3f gazeDirection1(0, 0, -1);
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// If tracking succeeded and we have an eye model, estimate gaze
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if (detection_success && face_model.eye_model)
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{
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GazeAnalysis::EstimateGaze(face_model, gazeDirection0, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy, true);
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GazeAnalysis::EstimateGaze(face_model, gazeDirection1, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy, false);
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}
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// Work out the pose of the head from the tracked model
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cv::Vec6d pose_estimate = LandmarkDetector::GetPose(face_model, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy);
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// Keeping track of FPS
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fps_tracker.AddFrame();
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// Displaying the tracking visualizations
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visualizer.SetImage(captured_image, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy);
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visualizer.SetObservationLandmarks(face_model.detected_landmarks, face_model.detection_certainty, face_model.GetVisibilities());
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visualizer.SetObservationPose(pose_estimate, face_model.detection_certainty);
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visualizer.SetObservationGaze(gazeDirection0, gazeDirection1, LandmarkDetector::CalculateAllEyeLandmarks(face_model), LandmarkDetector::Calculate3DEyeLandmarks(face_model, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy), face_model.detection_certainty);
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visualizer.SetFps(fps_tracker.GetFPS());
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// detect key presses (due to pecularities of OpenCV, you can get it when displaying images)
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char character_press = visualizer.ShowObservation();
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// restart the tracker
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if (character_press == 'r')
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{
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face_model.Reset();
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}
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// quit the application
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else if (character_press == 'q')
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{
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return(0);
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}
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// Grabbing the next frame in the sequence
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captured_image = sequence_reader.GetNextFrame();
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}
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// Reset the model, for the next video
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face_model.Reset();
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sequence_number++;
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}
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return 0;
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}
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