2016-05-20 20:48:43 +00:00
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///////////////////////////////////////////////////////////////////////////////
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2017-05-15 18:55:18 +00:00
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// Copyright (C) 2017, Carnegie Mellon University and University of Cambridge,
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2016-05-20 20:48:43 +00:00
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// all rights reserved.
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//
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2017-05-15 18:55:18 +00:00
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// ACADEMIC OR NON-PROFIT ORGANIZATION NONCOMMERCIAL RESEARCH USE ONLY
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2016-05-20 20:48:43 +00:00
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//
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2017-05-15 18:55:18 +00:00
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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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2016-05-20 20:48:43 +00:00
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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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namespace OpenFaceOffline
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{
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public class FpsTracker
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{
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public TimeSpan HistoryLength { get; set; }
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public FpsTracker()
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{
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HistoryLength = TimeSpan.FromSeconds(2);
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}
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private Queue<DateTime> frameTimes = new Queue<DateTime>();
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private void DiscardOldFrames()
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{
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while (frameTimes.Count > 0 && (MainWindow.CurrentTime - frameTimes.Peek()) > HistoryLength)
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frameTimes.Dequeue();
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}
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public void AddFrame()
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{
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frameTimes.Enqueue(MainWindow.CurrentTime);
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DiscardOldFrames();
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}
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public double GetFPS()
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{
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DiscardOldFrames();
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if (frameTimes.Count == 0)
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return 0;
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return frameTimes.Count / (MainWindow.CurrentTime - frameTimes.Peek()).TotalSeconds;
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}
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}
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}
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