548 lines
20 KiB
C#
548 lines
20 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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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text;
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using System.Threading.Tasks;
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using System.Windows;
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using System.Windows.Controls;
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using System.Windows.Data;
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using System.Windows.Documents;
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using System.Windows.Input;
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using System.Windows.Media;
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using System.Windows.Media.Imaging;
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using System.Windows.Navigation;
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using System.Windows.Shapes;
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using System.Threading;
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// Internal libraries
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using OpenFaceOffline;
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using OpenCVWrappers;
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using CppInterop;
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using CppInterop.LandmarkDetector;
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using CameraInterop;
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using FaceAnalyser_Interop;
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using System.Windows.Threading;
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using System.Diagnostics;
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namespace OpenFaceDemo
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{
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/// <summary>
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/// Interaction logic for MainWindow.xaml
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/// </summary>
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public partial class MainWindow : Window
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{
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// -----------------------------------------------------------------
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// Members
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// -----------------------------------------------------------------
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// Timing for measuring FPS
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#region High-Resolution Timing
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static DateTime startTime;
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static Stopwatch sw = new Stopwatch();
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static MainWindow()
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{
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startTime = DateTime.Now;
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sw.Start();
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}
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public static DateTime CurrentTime
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{
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get { return startTime + sw.Elapsed; }
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}
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#endregion
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Thread processing_thread;
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// Some members for displaying the results
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private Capture capture;
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private WriteableBitmap latest_img;
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private volatile bool thread_running;
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FpsTracker processing_fps = new FpsTracker();
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// Controlling the model reset
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volatile bool detectionSucceeding = false;
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volatile bool reset = false;
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Point? resetPoint = null;
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// For selecting webcams
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CameraSelection cam_sec;
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// For tracking
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FaceModelParameters clnf_params;
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CLNF clnf_model;
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FaceAnalyserManaged face_analyser;
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public MainWindow()
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{
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InitializeComponent();
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// Set the icon
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Uri iconUri = new Uri("logo1.ico", UriKind.RelativeOrAbsolute);
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this.Icon = BitmapFrame.Create(iconUri);
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String root = AppDomain.CurrentDomain.BaseDirectory;
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clnf_params = new FaceModelParameters(root, true);
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clnf_model = new CLNF(clnf_params);
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face_analyser = new FaceAnalyserManaged(root, true, 112);
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Dispatcher.Invoke(DispatcherPriority.Render, new TimeSpan(0, 0, 0, 0, 200), (Action)(() =>
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{
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headPosePlot.AssocColor(0, Colors.Blue);
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headPosePlot.AssocColor(1, Colors.Red);
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headPosePlot.AssocColor(2, Colors.Green);
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headPosePlot.AssocName(1, "Turn");
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headPosePlot.AssocName(2, "Tilt");
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headPosePlot.AssocName(0, "Up/Down");
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headPosePlot.AssocThickness(0, 2);
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headPosePlot.AssocThickness(1, 2);
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headPosePlot.AssocThickness(2, 2);
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gazePlot.AssocColor(0, Colors.Red);
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gazePlot.AssocColor(1, Colors.Blue);
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gazePlot.AssocName(0, "Left-right");
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gazePlot.AssocName(1, "Up-down");
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gazePlot.AssocThickness(0, 2);
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gazePlot.AssocThickness(1, 2);
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smilePlot.AssocColor(0, Colors.Green);
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smilePlot.AssocColor(1, Colors.Red);
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smilePlot.AssocName(0, "Smile");
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smilePlot.AssocName(1, "Frown");
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smilePlot.AssocThickness(0, 2);
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smilePlot.AssocThickness(1, 2);
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browPlot.AssocColor(0, Colors.Green);
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browPlot.AssocColor(1, Colors.Red);
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browPlot.AssocName(0, "Raise");
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browPlot.AssocName(1, "Furrow");
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browPlot.AssocThickness(0, 2);
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browPlot.AssocThickness(1, 2);
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eyePlot.AssocColor(0, Colors.Green);
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eyePlot.AssocColor(1, Colors.Red);
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eyePlot.AssocName(0, "Eye widen");
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eyePlot.AssocName(1, "Nose wrinkle");
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eyePlot.AssocThickness(0, 2);
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eyePlot.AssocThickness(1, 2);
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}));
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}
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private void StopTracking()
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{
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// First complete the running of the thread
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if (processing_thread != null)
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{
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// Tell the other thread to finish
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thread_running = false;
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processing_thread.Join();
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}
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}
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// The main function call for processing images, video files or webcam feed
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private void ProcessingLoop(int cam_id = -1, int width = -1, int height = -1, bool multi_face = false)
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{
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thread_running = true;
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// Create the video capture from a webcam and call the VideoLoop
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capture = new Capture(cam_id, width, height);
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if (capture.isOpened())
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{
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// Start the actual processing
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VideoLoop();
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}
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else
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{
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string messageBoxText = "Failed to open a webcam";
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string caption = "Webcam failure";
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MessageBoxButton button = MessageBoxButton.OK;
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MessageBoxImage icon = MessageBoxImage.Warning;
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// Display message box
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MessageBox.Show(messageBoxText, caption, button, icon);
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}
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}
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// Capturing and processing the video frame by frame
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private void VideoLoop()
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{
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Thread.CurrentThread.IsBackground = true;
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DateTime? startTime = CurrentTime;
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var lastFrameTime = CurrentTime;
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clnf_model.Reset();
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face_analyser.Reset();
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double fx, fy, cx, cy;
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fx = 500.0;
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fy = 500.0;
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cx = cy = -1;
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int frame_id = 0;
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double old_gaze_x = 0;
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double old_gaze_y = 0;
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double smile_cumm = 0;
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double frown_cumm = 0;
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double brow_up_cumm = 0;
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double brow_down_cumm = 0;
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double widen_cumm = 0;
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double wrinkle_cumm = 0;
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while (thread_running)
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{
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//////////////////////////////////////////////
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// CAPTURE FRAME AND DETECT LANDMARKS FOLLOWED BY THE REQUIRED IMAGE PROCESSING
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//////////////////////////////////////////////
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RawImage frame = null;
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double progress = -1;
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frame = new RawImage(capture.GetNextFrame(true));
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progress = capture.GetProgress();
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if (frame.Width == 0)
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{
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// This indicates that we reached the end of the video file
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break;
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}
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lastFrameTime = CurrentTime;
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processing_fps.AddFrame();
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var grayFrame = new RawImage(capture.GetCurrentFrameGray());
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if (grayFrame == null)
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{
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Console.WriteLine("Gray is empty");
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continue;
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}
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// This is more ore less guess work, but seems to work well enough
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if (cx == -1)
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{
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fx = fx * (grayFrame.Width / 640.0);
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fy = fy * (grayFrame.Height / 480.0);
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fx = (fx + fy) / 2.0;
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fy = fx;
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cx = grayFrame.Width / 2f;
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cy = grayFrame.Height / 2f;
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}
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bool detectionSucceeding = ProcessFrame(clnf_model, clnf_params, frame, grayFrame, fx, fy, cx, cy);
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double confidence = (-clnf_model.GetConfidence()) / 2.0 + 0.5;
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if (confidence < 0)
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confidence = 0;
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else if (confidence > 1)
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confidence = 1;
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List<double> pose = new List<double>();
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clnf_model.GetPose(pose, fx, fy, cx, cy);
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List<double> non_rigid_params = clnf_model.GetNonRigidParams();
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double scale = clnf_model.GetRigidParams()[0];
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double time_stamp = (DateTime.Now - (DateTime)startTime).TotalMilliseconds;
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// The face analysis step (only done if recording AUs, HOGs or video)
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face_analyser.AddNextFrame(frame, clnf_model, fx, fy, cx, cy, true, false, false);
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List<Tuple<Point, Point>> lines = null;
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List<Tuple<double, double>> landmarks = null;
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List<Tuple<double, double>> eye_landmarks = null;
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List<Tuple<Point, Point>> gaze_lines = null;
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Tuple<double, double> gaze_angle = face_analyser.GetGazeAngle();
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if (detectionSucceeding)
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{
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landmarks = clnf_model.CalculateLandmarks();
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eye_landmarks = clnf_model.CalculateEyeLandmarks();
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lines = clnf_model.CalculateBox((float)fx, (float)fy, (float)cx, (float)cy);
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gaze_lines = face_analyser.CalculateGazeLines(scale, (float)fx, (float)fy, (float)cx, (float)cy);
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}
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// Visualisation
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Dispatcher.Invoke(DispatcherPriority.Render, new TimeSpan(0, 0, 0, 0, 200), (Action)(() =>
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{
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var au_regs = face_analyser.GetCurrentAUsReg();
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double smile = (au_regs["AU12"] + au_regs["AU06"] + au_regs["AU25"]) / 13.0;
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double frown = (au_regs["AU15"] + au_regs["AU17"]) / 12.0;
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double brow_up = (au_regs["AU01"] + au_regs["AU02"]) / 10.0;
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double brow_down = au_regs["AU04"] / 5.0;
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double eye_widen = au_regs["AU05"] / 3.0;
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double nose_wrinkle = au_regs["AU09"] / 4.0;
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Dictionary<int, double> smileDict = new Dictionary<int, double>();
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smileDict[0] = 0.7 * smile_cumm + 0.3 * smile;
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smileDict[1] = 0.7 * frown_cumm + 0.3 * frown;
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smilePlot.AddDataPoint(new DataPointGraph() { Time = CurrentTime, values = smileDict, Confidence = confidence });
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Dictionary<int, double> browDict = new Dictionary<int, double>();
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browDict[0] = 0.7 * brow_up_cumm + 0.3 * brow_up;
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browDict[1] = 0.7 * brow_down_cumm + 0.3 * brow_down;
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browPlot.AddDataPoint(new DataPointGraph() { Time = CurrentTime, values = browDict, Confidence = confidence });
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Dictionary<int, double> eyeDict = new Dictionary<int, double>();
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eyeDict[0] = 0.7 * widen_cumm + 0.3 * eye_widen;
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eyeDict[1] = 0.7 * wrinkle_cumm + 0.3 * nose_wrinkle;
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eyePlot.AddDataPoint(new DataPointGraph() { Time = CurrentTime, values = eyeDict, Confidence = confidence });
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smile_cumm = smileDict[0];
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frown_cumm = smileDict[1];
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brow_up_cumm = browDict[0];
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brow_down_cumm = browDict[1];
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widen_cumm = eyeDict[0];
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wrinkle_cumm = eyeDict[1];
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Dictionary<int, double> poseDict = new Dictionary<int, double>();
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poseDict[0] = -pose[3];
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poseDict[1] = pose[4];
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poseDict[2] = pose[5];
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headPosePlot.AddDataPoint(new DataPointGraph() { Time = CurrentTime, values = poseDict, Confidence = confidence });
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Dictionary<int, double> gazeDict = new Dictionary<int, double>();
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gazeDict[0] = gaze_angle.Item1 * (180.0 / Math.PI);
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gazeDict[0] = 0.5 * old_gaze_x + 0.5 * gazeDict[0];
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gazeDict[1] = -gaze_angle.Item2 * (180.0 / Math.PI);
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gazeDict[1] = 0.5 * old_gaze_y + 0.5 * gazeDict[1];
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gazePlot.AddDataPoint(new DataPointGraph() { Time = CurrentTime, values = gazeDict, Confidence = confidence });
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old_gaze_x = gazeDict[0];
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old_gaze_y = gazeDict[1];
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if (latest_img == null)
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{
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latest_img = frame.CreateWriteableBitmap();
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}
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frame.UpdateWriteableBitmap(latest_img);
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video.Source = latest_img;
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video.Confidence = confidence;
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video.FPS = processing_fps.GetFPS();
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video.Progress = progress;
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if (!detectionSucceeding)
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{
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video.OverlayLines.Clear();
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video.OverlayPoints.Clear();
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video.OverlayEyePoints.Clear();
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video.GazeLines.Clear();
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}
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else
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{
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video.OverlayLines = lines;
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List<Point> landmark_points = new List<Point>();
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foreach (var p in landmarks)
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{
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landmark_points.Add(new Point(p.Item1, p.Item2));
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}
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List<Point> eye_landmark_points = new List<Point>();
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foreach (var p in eye_landmarks)
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{
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eye_landmark_points.Add(new Point(p.Item1, p.Item2));
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}
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video.OverlayPoints = landmark_points;
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video.OverlayEyePoints = eye_landmark_points;
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video.GazeLines = gaze_lines;
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}
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}));
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if (reset)
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{
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if (resetPoint.HasValue)
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{
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clnf_model.Reset(resetPoint.Value.X, resetPoint.Value.Y);
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resetPoint = null;
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}
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else
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{
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clnf_model.Reset();
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}
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face_analyser.Reset();
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reset = false;
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Dispatcher.Invoke(DispatcherPriority.Render, new TimeSpan(0, 0, 0, 0, 200), (Action)(() =>
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{
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headPosePlot.ClearDataPoints();
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headPosePlot.ClearDataPoints();
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gazePlot.ClearDataPoints();
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smilePlot.ClearDataPoints();
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browPlot.ClearDataPoints();
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eyePlot.ClearDataPoints();
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}));
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}
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frame_id++;
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}
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latest_img = null;
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}
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private bool ProcessFrame(CLNF clnf_model, FaceModelParameters clnf_params, RawImage frame, RawImage grayscale_frame, double fx, double fy, double cx, double cy)
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{
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detectionSucceeding = clnf_model.DetectLandmarksInVideo(grayscale_frame, clnf_params);
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return detectionSucceeding;
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}
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// --------------------------------------------------------
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// Button handling
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// --------------------------------------------------------
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private void openWebcamClick(object sender, RoutedEventArgs e)
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{
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new Thread(() => openWebcam()).Start();
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}
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private void openWebcam()
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{
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StopTracking();
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Dispatcher.Invoke(DispatcherPriority.Render, new TimeSpan(0, 0, 0, 2, 0), (Action)(() =>
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{
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// First close the cameras that might be open to avoid clashing with webcam opening
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if (capture != null)
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{
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capture.Dispose();
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}
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if (cam_sec == null)
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{
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cam_sec = new CameraSelection();
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}
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else
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{
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cam_sec = new CameraSelection(cam_sec.cams);
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cam_sec.Visibility = System.Windows.Visibility.Visible;
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}
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// Set the icon
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Uri iconUri = new Uri("logo1.ico", UriKind.RelativeOrAbsolute);
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cam_sec.Icon = BitmapFrame.Create(iconUri);
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if (!cam_sec.no_cameras_found)
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cam_sec.ShowDialog();
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if (cam_sec.camera_selected)
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{
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int cam_id = cam_sec.selected_camera.Item1;
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int width = cam_sec.selected_camera.Item2;
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int height = cam_sec.selected_camera.Item3;
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processing_thread = new Thread(() => ProcessingLoop(cam_id, width, height));
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processing_thread.Start();
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}
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}));
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}
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// Cleanup stuff when closing the window
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private void Window_Closing(object sender, System.ComponentModel.CancelEventArgs e)
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{
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if (processing_thread != null)
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{
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// Stop capture and tracking
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thread_running = false;
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processing_thread.Join();
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if (capture != null)
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capture.Dispose();
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}
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if (face_analyser != null)
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face_analyser.Dispose();
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if(clnf_model != null)
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clnf_model.Dispose();
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}
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private void Window_KeyDown(object sender, KeyEventArgs e)
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{
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if (e.Key == Key.R)
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{
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reset = true;
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}
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}
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private void video_MouseDown(object sender, MouseButtonEventArgs e)
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{
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var clickPos = e.GetPosition(video);
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resetPoint = new Point(clickPos.X / video.ActualWidth, clickPos.Y / video.ActualHeight);
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reset = true;
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}
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|
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}
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}
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