300 lines
12 KiB
C#
300 lines
12 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 CppInterop.LandmarkDetector;
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using FaceAnalyser_Interop;
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using GazeAnalyser_Interop;
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using System;
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using System.Collections.Generic;
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using System.IO;
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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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namespace OpenFaceOffline
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{
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class Recorder
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{
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StreamWriter output_features_file;
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bool output_2D_landmarks, output_3D_landmarks, output_model_params, output_pose, output_AUs, output_gaze, record_aligned, record_HOG;
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double fx, fy, cx, cy;
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List<string> au_reg_names;
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List<string> au_class_names;
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String out_filename;
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bool dynamic_AU_model;
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public Recorder(string root, string filename, int width, int height, bool output_2D_landmarks, bool output_3D_landmarks, bool output_model_params,
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bool output_pose, bool output_AUs, bool output_gaze, bool record_aligned, bool record_HOG,
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CLNF clnf_model, FaceAnalyserManaged face_analyser, double fx, double fy, double cx, double cy, bool dynamic_AU_model)
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{
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this.output_2D_landmarks = output_2D_landmarks; this.output_3D_landmarks = output_3D_landmarks;
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this.output_model_params = output_model_params; this.output_pose = output_pose;
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this.output_AUs = output_AUs; this.output_gaze = output_gaze;
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this.record_aligned = record_aligned; this.record_HOG = record_HOG;
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this.fx = fx; this.fy = fy; this.cx = cx; this.cy = cy;
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this.dynamic_AU_model = dynamic_AU_model;
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if (!System.IO.Directory.Exists(root))
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{
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System.IO.Directory.CreateDirectory(root);
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}
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// Write out the OF file which tells where all the relevant data is
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StreamWriter out_of_file = new StreamWriter(root + "/" + filename + ".of");
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//out_of_file.WriteLine("Video_file:" + )
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out_of_file.WriteLine("CSV file: " + root + "/" + filename + ".csv");
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if(record_HOG)
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{
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out_of_file.WriteLine("HOG file: " + root + "/" + filename + ".hog");
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}
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if(record_aligned)
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{
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out_of_file.WriteLine("Aligned dir: " + root + "/" + filename + "/");
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}
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out_filename = root + "/" + filename + ".csv";
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output_features_file = new StreamWriter(out_filename);
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output_features_file.Write("frame, timestamp, confidence, success");
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if (output_gaze)
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{
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output_features_file.Write(", gaze_0_x, gaze_0_y, gaze_0_z, gaze_1_x, gaze_1_y, gaze_1_z, gaze_angle_x, gaze_angle_y");
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// Output gaze eye landmarks
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int gaze_num_lmks = clnf_model.CalculateAllEyeLandmarks().Count;
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for (int i = 0; i < gaze_num_lmks; ++i)
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{
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output_features_file.Write(", eye_lmk_x_" + i);
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}
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for (int i = 0; i < gaze_num_lmks; ++i)
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{
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output_features_file.Write(", eye_lmk_y_" + i);
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}
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}
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if (output_pose)
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output_features_file.Write(", pose_Tx, pose_Ty, pose_Tz, pose_Rx, pose_Ry, pose_Rz");
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if (output_2D_landmarks)
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{
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for (int i = 0; i < clnf_model.GetNumPoints(); ++i)
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{
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output_features_file.Write(", x_" + i);
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}
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for (int i = 0; i < clnf_model.GetNumPoints(); ++i)
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{
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output_features_file.Write(", y_" + i);
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}
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}
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if (output_3D_landmarks)
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{
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for (int i = 0; i < clnf_model.GetNumPoints(); ++i)
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{
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output_features_file.Write(", X_" + i);
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}
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for (int i = 0; i < clnf_model.GetNumPoints(); ++i)
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{
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output_features_file.Write(", Y_" + i);
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}
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for (int i = 0; i < clnf_model.GetNumPoints(); ++i)
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{
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output_features_file.Write(", Z_" + i);
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}
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}
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if (output_model_params)
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{
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output_features_file.Write(", p_scale, p_rx, p_ry, p_rz, p_tx, p_ty");
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for (int i = 0; i < clnf_model.GetNumModes(); ++i)
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{
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output_features_file.Write(", p_" + i);
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}
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}
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if (output_AUs)
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{
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au_reg_names = face_analyser.GetRegActionUnitsNames();
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au_reg_names.Sort();
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foreach (var name in au_reg_names)
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{
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output_features_file.Write(", " + name + "_r");
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}
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au_class_names = face_analyser.GetClassActionUnitsNames();
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au_class_names.Sort();
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foreach (var name in au_class_names)
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{
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output_features_file.Write(", " + name + "_c");
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}
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}
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output_features_file.WriteLine();
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if (record_aligned)
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{
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String aligned_root = root + "/" + filename + "_aligned/";
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System.IO.Directory.CreateDirectory(aligned_root);
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face_analyser.SetupAlignedImageRecording(aligned_root);
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}
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if (record_HOG)
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{
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String filename_HOG = root + "/" + filename + ".hog";
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face_analyser.SetupHOGRecording(filename_HOG);
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}
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}
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public void RecordFrame(CLNF clnf_model, FaceAnalyserManaged face_analyser, GazeAnalyserManaged gaze_analyser, bool success, int frame_ind, double time_stamp)
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{
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// Making sure that full stop is used instead of a comma for data recording
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System.Globalization.CultureInfo customCulture = (System.Globalization.CultureInfo)System.Threading.Thread.CurrentThread.CurrentCulture.Clone();
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customCulture.NumberFormat.NumberDecimalSeparator = ".";
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System.Threading.Thread.CurrentThread.CurrentCulture = customCulture;
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double confidence = (-clnf_model.GetConfidence()) / 2.0 + 0.5;
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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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output_features_file.Write(String.Format("{0}, {1}, {2:F3}, {3}", frame_ind, time_stamp, confidence, success ? 1 : 0));
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if (output_gaze)
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{
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var gaze = gaze_analyser.GetGazeCamera();
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var gaze_angle = gaze_analyser.GetGazeAngle();
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output_features_file.Write(String.Format(", {0:F5}, {1:F5}, {2:F5}, {3:F5}, {4:F5}, {5:F5}, {6:F5}, {7:F5}", gaze.Item1.Item1, gaze.Item1.Item2, gaze.Item1.Item3,
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gaze.Item2.Item1, gaze.Item2.Item2, gaze.Item2.Item3, gaze_angle.Item1, gaze_angle.Item2));
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List<Tuple<double, double>> landmarks_2d = clnf_model.CalculateAllEyeLandmarks();
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for (int i = 0; i < landmarks_2d.Count; ++i)
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output_features_file.Write(", {0:F2}", landmarks_2d[i].Item1);
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for (int i = 0; i < landmarks_2d.Count; ++i)
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output_features_file.Write(", {0:F2}", landmarks_2d[i].Item2);
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}
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if (output_pose)
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output_features_file.Write(String.Format(", {0:F4}, {1:F4}, {2:F4}, {3:F4}, {4:F4}, {5:F4}", pose[0], pose[1], pose[2], pose[3], pose[4], pose[5]));
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if (output_2D_landmarks)
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{
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List<Tuple<double, double>> landmarks_2d = clnf_model.CalculateAllLandmarks();
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for (int i = 0; i < landmarks_2d.Count; ++i)
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output_features_file.Write(", {0:F2}", landmarks_2d[i].Item1);
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for (int i = 0; i < landmarks_2d.Count; ++i)
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output_features_file.Write(", {0:F2}", landmarks_2d[i].Item2);
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}
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if (output_3D_landmarks)
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{
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List<System.Windows.Media.Media3D.Point3D> landmarks_3d = clnf_model.Calculate3DLandmarks(fx, fy, cx, cy);
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for (int i = 0; i < landmarks_3d.Count; ++i)
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output_features_file.Write(", {0:F2}", landmarks_3d[i].X);
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for (int i = 0; i < landmarks_3d.Count; ++i)
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output_features_file.Write(", {0:F2}", landmarks_3d[i].Y);
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for (int i = 0; i < landmarks_3d.Count; ++i)
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output_features_file.Write(", {0:F2}", landmarks_3d[i].Z);
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}
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if (output_model_params)
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{
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List<double> all_params = clnf_model.GetParams();
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for (int i = 0; i < all_params.Count; ++i)
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output_features_file.Write(String.Format(", {0,0:F5}", all_params[i]));
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}
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if (output_AUs)
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{
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var au_regs = face_analyser.GetCurrentAUsReg();
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foreach (var name_reg in au_reg_names)
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output_features_file.Write(", {0:F2}", au_regs[name_reg]);
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var au_classes = face_analyser.GetCurrentAUsClass();
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foreach (var name_class in au_class_names)
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output_features_file.Write(", {0:F0}", au_classes[name_class]);
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}
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output_features_file.WriteLine();
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if (record_aligned)
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{
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face_analyser.RecordAlignedFrame(frame_ind);
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}
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if (record_HOG)
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{
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face_analyser.RecordHOGFrame();
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}
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}
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public void FinishRecording(CLNF clnf_model, FaceAnalyserManaged face_analyser)
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{
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if (output_features_file != null)
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output_features_file.Close();
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if (record_HOG)
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face_analyser.StopHOGRecording();
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face_analyser.PostProcessOutputFile(out_filename);
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}
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}
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}
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