Interface changes to provide multi output support, also enforcing parameters in executables.
This commit is contained in:
parent
aba6ea646b
commit
a4de1d42a5
11 changed files with 179 additions and 75 deletions
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@ -85,6 +85,14 @@ int main (int argc, char **argv)
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//Convert arguments to more convenient vector form
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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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// Prepare for image reading
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Utilities::ImageCapture image_reader;
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@ -205,6 +213,7 @@ int main (int argc, char **argv)
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open_face_rec.SetObservationPose(pose_estimate);
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open_face_rec.SetObservationGaze(gaze_direction0, gaze_direction1, gaze_angle, LandmarkDetector::CalculateAllEyeLandmarks(face_model), LandmarkDetector::Calculate3DEyeLandmarks(face_model, image_reader.fx, image_reader.fy, image_reader.cx, image_reader.cy));
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open_face_rec.SetObservationFaceAlign(sim_warped_img);
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open_face_rec.SetObservationFaceID(face);
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open_face_rec.WriteObservation();
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}
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@ -39,6 +39,10 @@
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#include "VisualizationUtils.h"
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#include "Visualizer.h"
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#include "SequenceCapture.h"
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#include <RecorderOpenFace.h>
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#include <RecorderOpenFaceParameters.h>
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#include <GazeEstimation.h>
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#include <FaceAnalyser.h>
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#include <fstream>
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#include <sstream>
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@ -110,7 +114,14 @@ int main (int argc, char **argv)
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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_params(arguments);
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// This is so that the model would not try re-initialising itself
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det_params.reinit_video_every = -1;
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@ -142,11 +153,16 @@ int main (int argc, char **argv)
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det_parameters.push_back(det_params);
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}
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// Load facial feature extractor and AU analyser (make sure it is static, as we don't reidentify faces)
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FaceAnalysis::FaceAnalyserParameters face_analysis_params(arguments);
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face_analysis_params.OptimizeForImages();
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FaceAnalysis::FaceAnalyser face_analyser(face_analysis_params);
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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);
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Utilities::Visualizer visualizer(arguments);
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// Tracking FPS for visualization
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Utilities::FpsTracker fps_tracker;
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@ -159,46 +175,41 @@ int main (int argc, char **argv)
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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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{
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// If failed to open because no input files specified, attempt to open a webcam
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if (sequence_reader.no_input_specified && sequence_number == 0)
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{
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// If that fails, revert to webcam
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INFO_STREAM("No input specified, attempting to open a webcam 0");
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if (!sequence_reader.OpenWebcam(0))
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{
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ERROR_STREAM("Failed to open the webcam");
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break;
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}
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}
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else
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{
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break;
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}
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}
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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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int frame_count = 0;
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Utilities::RecorderOpenFaceParameters recording_params(arguments, true, sequence_reader.IsWebcam(),
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sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy, sequence_reader.fps);
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// Do not do AU detection on multi-face case as it is not supported
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recording_params.setOutputAUs(false);
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Utilities::RecorderOpenFace open_face_rec(sequence_reader.name, recording_params, arguments);
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if (recording_params.outputGaze() && !face_model.eye_model)
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cout << "WARNING: no eye model defined, but outputting gaze" << endl;
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if (sequence_reader.IsWebcam())
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{
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INFO_STREAM("WARNING: using a webcam in feature extraction, forcing visualization of tracking to allow quitting the application (press q)");
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visualizer.vis_track = true;
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}
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if (recording_params.outputAUs())
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{
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INFO_STREAM("WARNING: using a AU detection in multiple face mode, it might not be as accurate and is experimental");
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}
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INFO_STREAM( "Starting tracking");
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while(!captured_image.empty())
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{
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// Reading the images
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cv::Mat_<uchar> grayscale_image;
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cv::Mat disp_image = captured_image.clone();
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if(captured_image.channels() == 3)
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{
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cv::cvtColor(captured_image, grayscale_image, CV_BGR2GRAY);
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}
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else
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{
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grayscale_image = captured_image.clone();
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}
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cv::Mat_<uchar> grayscale_image = sequence_reader.GetGrayFrame();
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vector<cv::Rect_<double> > face_detections;
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@ -261,7 +272,7 @@ int main (int argc, char **argv)
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// This ensures that a wider window is used for the initial landmark localisation
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face_models[model].detection_success = false;
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detection_success = LandmarkDetector::DetectLandmarksInVideo(grayscale_image, face_detections[detection_ind], face_models[model], det_parameters[model]);
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// This activates the model
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active_models[model] = true;
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@ -283,14 +294,60 @@ int main (int argc, char **argv)
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visualizer.SetImage(captured_image, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy);
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// Go through every model and visualise the results
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// Go through every model and detect eye gaze, record results and visualise the results
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for(size_t model = 0; model < face_models.size(); ++model)
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{
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// Visualising the results
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if(active_models[model])
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{
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// Estimate head pose and eye gaze
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cv::Vec6d pose_estimate = LandmarkDetector::GetPose(face_models[model], sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy);
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cv::Point3f gaze_direction0(0, 0, 0); cv::Point3f gaze_direction1(0, 0, 0); cv::Vec2d gaze_angle(0, 0);
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// Detect eye gazes
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if (face_models[model].detection_success && face_model.eye_model)
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{
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GazeAnalysis::EstimateGaze(face_models[model], gaze_direction0, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy, true);
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GazeAnalysis::EstimateGaze(face_models[model], gaze_direction1, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy, false);
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gaze_angle = GazeAnalysis::GetGazeAngle(gaze_direction0, gaze_direction1);
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}
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// Face analysis step
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cv::Mat sim_warped_img;
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cv::Mat_<double> hog_descriptor; int num_hog_rows = 0, num_hog_cols = 0;
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// Perform AU detection and HOG feature extraction, as this can be expensive only compute it if needed by output or visualization
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if (recording_params.outputAlignedFaces() || recording_params.outputHOG() || recording_params.outputAUs() || visualizer.vis_align || visualizer.vis_hog)
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{
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face_analyser.PredictStaticAUsAndComputeFeatures(captured_image, face_models[model].detected_landmarks);
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face_analyser.GetLatestAlignedFace(sim_warped_img);
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face_analyser.GetLatestHOG(hog_descriptor, num_hog_rows, num_hog_cols);
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}
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// Visualize the features
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visualizer.SetObservationFaceAlign(sim_warped_img);
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visualizer.SetObservationHOG(hog_descriptor, num_hog_rows, num_hog_cols);
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visualizer.SetObservationLandmarks(face_models[model].detected_landmarks, face_models[model].detection_certainty);
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visualizer.SetObservationPose(LandmarkDetector::GetPose(face_models[model], sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy), face_models[model].detection_certainty);
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visualizer.SetObservationGaze(gaze_direction0, gaze_direction1, LandmarkDetector::CalculateAllEyeLandmarks(face_models[model]), LandmarkDetector::Calculate3DEyeLandmarks(face_models[model], sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy), face_models[model].detection_certainty);
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// Output features
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open_face_rec.SetObservationHOG(face_models[model].detection_success, hog_descriptor, num_hog_rows, num_hog_cols, 31); // The number of channels in HOG is fixed at the moment, as using FHOG
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open_face_rec.SetObservationVisualization(visualizer.GetVisImage());
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open_face_rec.SetObservationActionUnits(face_analyser.GetCurrentAUsReg(), face_analyser.GetCurrentAUsClass());
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open_face_rec.SetObservationLandmarks(face_models[model].detected_landmarks, face_models[model].GetShape(sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy),
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face_models[model].params_global, face_models[model].params_local, face_models[model].detection_certainty, face_models[model].detection_success);
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open_face_rec.SetObservationPose(pose_estimate);
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open_face_rec.SetObservationGaze(gaze_direction0, gaze_direction1, gaze_angle, LandmarkDetector::CalculateAllEyeLandmarks(face_models[model]), LandmarkDetector::Calculate3DEyeLandmarks(face_models[model], sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy));
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open_face_rec.SetObservationFaceAlign(sim_warped_img);
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open_face_rec.SetObservationFaceID(model);
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open_face_rec.SetObservationTimestamp(sequence_reader.time_stamp);
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open_face_rec.SetObservationFrameNumber(sequence_reader.GetFrameNumber());
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open_face_rec.WriteObservation();
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}
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}
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visualizer.SetFps(fps_tracker.GetFPS());
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@ -103,6 +103,14 @@ int main (int argc, char **argv)
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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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// Load the modules that are being used for tracking and face analysis
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// Load face landmark detector
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LandmarkDetector::FaceModelParameters det_parameters(arguments);
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@ -217,6 +225,8 @@ int main (int argc, char **argv)
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open_face_rec.SetObservationPose(pose_estimate);
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open_face_rec.SetObservationGaze(gazeDirection0, gazeDirection1, gazeAngle, LandmarkDetector::CalculateAllEyeLandmarks(face_model), LandmarkDetector::Calculate3DEyeLandmarks(face_model, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy));
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open_face_rec.SetObservationTimestamp(sequence_reader.time_stamp);
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open_face_rec.SetObservationFaceID(0);
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open_face_rec.SetObservationFrameNumber(sequence_reader.GetFrameNumber());
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open_face_rec.SetObservationFaceAlign(sim_warped_img);
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open_face_rec.WriteObservation();
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@ -60,10 +60,12 @@ namespace Utilities
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bool Open(std::string output_file_name, bool is_sequence, bool output_2D_landmarks, bool output_3D_landmarks, bool output_model_params, bool output_pose, bool output_AUs, bool output_gaze,
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int num_face_landmarks, int num_model_modes, int num_eye_landmarks, const std::vector<std::string>& au_names_class, const std::vector<std::string>& au_names_reg);
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bool isOpen() const { return output_file.is_open(); }
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// Closing the file and cleaning up
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void Close();
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void WriteLine(int observation_count, double time_stamp, bool landmark_detection_success, double landmark_confidence,
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void WriteLine(int face_id, int frame_num, double time_stamp, bool landmark_detection_success, double landmark_confidence,
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const cv::Mat_<double>& landmarks_2D, const cv::Mat_<double>& landmarks_3D, const cv::Mat_<double>& pdm_model_params, const cv::Vec6d& rigid_shape_params, cv::Vec6d& pose_estimate,
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const cv::Point3f& gazeDirection0, const cv::Point3f& gazeDirection1, const cv::Vec2d& gaze_angle, const std::vector<cv::Point2d>& eye_landmarks2d, const std::vector<cv::Point3d>& eye_landmarks3d,
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const std::vector<std::pair<std::string, double> >& au_intensities, const std::vector<std::pair<std::string, double> >& au_occurences);
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@ -70,6 +70,12 @@ namespace Utilities
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// Required observations for video/image-sequence
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void SetObservationTimestamp(double timestamp);
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// Required observations for video/image-sequence
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void SetObservationFrameNumber(double frame_number);
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// If in multiple face mode, identifying which face was tracked
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void SetObservationFaceID(int face_id);
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// All observations relevant to facial landmarks
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void SetObservationLandmarks(const cv::Mat_<double>& landmarks_2D, const cv::Mat_<double>& landmarks_3D,
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const cv::Vec6d& params_global, const cv::Mat_<double>& params_local, double confidence, bool success);
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@ -123,7 +129,10 @@ namespace Utilities
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RecorderHOG hog_recorder;
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// The actual temporary storage for the observations
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double timestamp;
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int face_id;
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int frame_number;
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// Facial landmark related observations
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cv::Mat_<double> landmarks_2D;
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@ -147,7 +156,8 @@ namespace Utilities
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std::vector<cv::Point2d> eye_landmarks2D;
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std::vector<cv::Point3d> eye_landmarks3D;
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int observation_count;
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int m_frame_number; // TODO this should be set
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int m_face_id; // TODO this should be set
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// For video writing
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cv::VideoWriter video_writer;
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@ -77,6 +77,8 @@ namespace Utilities
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float getCx() const { return cx; }
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float getCy() const { return cy; }
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void setOutputAUs(bool output_AUs) { this->output_AUs = output_AUs; }
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private:
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// If we are recording results from a sequence each row refers to a frame, if we are recording an image each row is a face
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@ -85,6 +85,8 @@ namespace Utilities
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// Parameters describing the sequence and it's progress
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double GetProgress();
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int GetFrameNumber() { return frame_num; }
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bool IsOpened();
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void Close();
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@ -78,7 +78,7 @@ bool RecorderCSV::Open(std::string output_file_name, bool is_sequence, bool outp
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// Different headers if we are writing out the results on a sequence or an individual image
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if(this->is_sequence)
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{
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output_file << "frame, timestamp, confidence, success";
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output_file << "frame, face_id, timestamp, confidence, success";
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}
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else
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{
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@ -176,7 +176,7 @@ bool RecorderCSV::Open(std::string output_file_name, bool is_sequence, bool outp
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}
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void RecorderCSV::WriteLine(int observation_count, double time_stamp, bool landmark_detection_success, double landmark_confidence,
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void RecorderCSV::WriteLine(int face_id, int frame_num, double time_stamp, bool landmark_detection_success, double landmark_confidence,
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const cv::Mat_<double>& landmarks_2D, const cv::Mat_<double>& landmarks_3D, const cv::Mat_<double>& pdm_model_params, const cv::Vec6d& rigid_shape_params, cv::Vec6d& pose_estimate,
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const cv::Point3f& gazeDirection0, const cv::Point3f& gazeDirection1, const cv::Vec2d& gaze_angle, const std::vector<cv::Point2d>& eye_landmarks2d, const std::vector<cv::Point3d>& eye_landmarks3d,
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const std::vector<std::pair<std::string, double> >& au_intensities, const std::vector<std::pair<std::string, double> >& au_occurences)
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output_file << std::noshowpoint;
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if(is_sequence)
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{
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output_file << std::setprecision(3);
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output_file << observation_count << ", " << time_stamp;
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output_file << frame_num << ", " << face_id << ", " << time_stamp;
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output_file << std::setprecision(2);
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output_file << ", " << landmark_confidence;
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output_file << std::setprecision(0);
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@ -203,7 +204,7 @@ void RecorderCSV::WriteLine(int observation_count, double time_stamp, bool landm
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else
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{
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output_file << std::setprecision(3);
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output_file << observation_count << ", " << landmark_confidence;
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output_file << face_id << ", " << landmark_confidence;
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}
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// Output the estimated gaze
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if (output_gaze)
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@ -153,7 +153,7 @@ void RecorderOpenFace::PrepareRecording(const std::string& in_filename)
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CreateDirectory(aligned_output_directory);
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}
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observation_count = 0;
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this->frame_number = 0;
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}
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@ -275,11 +275,9 @@ void RecorderOpenFace::SetObservationVisualization(const cv::Mat &vis_track)
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void RecorderOpenFace::WriteObservation()
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{
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observation_count++;
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// Write out the CSV file (it will always be there, even if not outputting anything more but frame/face numbers)
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if(observation_count == 1)
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// Write out the CSV file (it will always be there, even if not outputting anything more but frame/face numbers)
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if(!csv_recorder.isOpen())
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{
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// As we are writing out the header, work out some things like number of landmarks, names of AUs etc.
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int num_face_landmarks = landmarks_2D.rows / 2;
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@ -315,7 +313,7 @@ void RecorderOpenFace::WriteObservation()
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params.outputAUs(), params.outputGaze(), num_face_landmarks, num_model_modes, num_eye_landmarks, au_names_class, au_names_reg);
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}
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this->csv_recorder.WriteLine(observation_count, timestamp, landmark_detection_success,
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this->csv_recorder.WriteLine(face_id, frame_number, timestamp, landmark_detection_success,
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landmark_detection_confidence, landmarks_2D, landmarks_3D, pdm_params_local, pdm_params_global, head_pose,
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gaze_direction0, gaze_direction1, gaze_angle, eye_landmarks2D, eye_landmarks3D, au_intensities, au_occurences);
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@ -331,9 +329,9 @@ void RecorderOpenFace::WriteObservation()
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// Filename is based on frame number
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if(params.isSequence())
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std::sprintf(name, "frame_det_%06d.bmp", observation_count);
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std::sprintf(name, "frame_det_%02d_%06d.bmp", face_id, frame_number);
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else
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std::sprintf(name, "face_det_%06d.bmp", observation_count);
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std::sprintf(name, "face_det_%06d.bmp", face_id);
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// Construct the output filename
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boost::filesystem::path slash("/");
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|
@ -387,6 +385,19 @@ void RecorderOpenFace::SetObservationTimestamp(double timestamp)
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this->timestamp = timestamp;
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}
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// Required observations for video/image-sequence
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void RecorderOpenFace::SetObservationFrameNumber(double frame_number)
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{
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this->frame_number = frame_number;
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}
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// If in multiple face mode, identifying which face was tracked
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void RecorderOpenFace::SetObservationFaceID(int face_id)
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{
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this->face_id = face_id;
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}
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void RecorderOpenFace::SetObservationLandmarks(const cv::Mat_<double>& landmarks_2D, const cv::Mat_<double>& landmarks_3D,
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const cv::Vec6d& pdm_params_global, const cv::Mat_<double>& pdm_params_local, double confidence, bool success)
|
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{
|
||||
|
|
|
@ -60,61 +60,61 @@ RecorderOpenFaceParameters::RecorderOpenFaceParameters(std::vector<std::string>
|
|||
|
||||
bool output_set = false;
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||||
|
||||
output_2D_landmarks = false;
|
||||
output_3D_landmarks = false;
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output_model_params = false;
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||||
output_pose = false;
|
||||
output_AUs = false;
|
||||
output_gaze = false;
|
||||
output_hog = false;
|
||||
output_tracked = false;
|
||||
output_aligned_faces = false;
|
||||
this->output_2D_landmarks = false;
|
||||
this->output_3D_landmarks = false;
|
||||
this->output_model_params = false;
|
||||
this->output_pose = false;
|
||||
this->output_AUs = false;
|
||||
this->output_gaze = false;
|
||||
this->output_hog = false;
|
||||
this->output_tracked = false;
|
||||
this->output_aligned_faces = false;
|
||||
|
||||
for (size_t i = 0; i < arguments.size(); ++i)
|
||||
{
|
||||
if (arguments[i].compare("-simalign") == 0)
|
||||
{
|
||||
output_aligned_faces = true;
|
||||
this->output_aligned_faces = true;
|
||||
output_set = true;
|
||||
}
|
||||
else if (arguments[i].compare("-hogalign") == 0)
|
||||
{
|
||||
output_hog = true;
|
||||
this->output_hog = true;
|
||||
output_set = true;
|
||||
}
|
||||
else if (arguments[i].compare("-2Dfp") == 0)
|
||||
{
|
||||
output_2D_landmarks = true;
|
||||
this->output_2D_landmarks = true;
|
||||
output_set = true;
|
||||
}
|
||||
else if (arguments[i].compare("-3Dfp") == 0)
|
||||
{
|
||||
output_3D_landmarks = true;
|
||||
this->output_3D_landmarks = true;
|
||||
output_set = true;
|
||||
}
|
||||
else if (arguments[i].compare("-pdmparams") == 0)
|
||||
{
|
||||
output_model_params = true;
|
||||
this->output_model_params = true;
|
||||
output_set = true;
|
||||
}
|
||||
else if (arguments[i].compare("-pose") == 0)
|
||||
{
|
||||
output_pose = true;
|
||||
this->output_pose = true;
|
||||
output_set = true;
|
||||
}
|
||||
else if (arguments[i].compare("-aus") == 0)
|
||||
{
|
||||
output_AUs = true;
|
||||
this->output_AUs = true;
|
||||
output_set = true;
|
||||
}
|
||||
else if (arguments[i].compare("-gaze") == 0)
|
||||
{
|
||||
output_gaze = true;
|
||||
this->output_gaze = true;
|
||||
output_set = true;
|
||||
}
|
||||
else if (arguments[i].compare("-tracked") == 0)
|
||||
{
|
||||
output_tracked = true;
|
||||
this->output_tracked = true;
|
||||
output_set = true;
|
||||
}
|
||||
}
|
||||
|
@ -123,15 +123,15 @@ RecorderOpenFaceParameters::RecorderOpenFaceParameters(std::vector<std::string>
|
|||
|
||||
if (!output_set)
|
||||
{
|
||||
output_2D_landmarks = true;
|
||||
output_3D_landmarks = true;
|
||||
output_model_params = true;
|
||||
output_pose = true;
|
||||
output_AUs = true;
|
||||
output_gaze = true;
|
||||
output_hog = true;
|
||||
output_tracked = true;
|
||||
output_aligned_faces = true;
|
||||
this->output_2D_landmarks = true;
|
||||
this->output_3D_landmarks = true;
|
||||
this->output_model_params = true;
|
||||
this->output_pose = true;
|
||||
this->output_AUs = true;
|
||||
this->output_gaze = true;
|
||||
this->output_hog = true;
|
||||
this->output_tracked = true;
|
||||
this->output_aligned_faces = true;
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
@ -19,7 +19,7 @@ model = 'model/main_clnf_general.txt'; % Trained on in the wild and multi-pie da
|
|||
%model = 'model/main_clm_wild.txt'; % Trained on in-the-wild
|
||||
|
||||
% Create a command that will run the tracker on set of videos and display the output
|
||||
command = sprintf('%s -mloc "%s" ', executable, model);
|
||||
command = sprintf('%s -mloc "%s" -verbose ', executable, model);
|
||||
|
||||
% add all videos to single argument list (so as not to load the model anew
|
||||
% for every video)
|
||||
|
|
Loading…
Reference in a new issue