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Fixing recorder and visualizer for FaceLandmarkImg

This commit is contained in:
Tadas Baltrusaitis 2017-11-16 17:46:34 +00:00
parent 734c4fd34d
commit dcb9d90eca
4 changed files with 42 additions and 11 deletions
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7
exe/FaceLandmarkImg/FaceLandmarkImg.cpp
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@ -248,7 +248,7 @@ int main (int argc, char **argv)
// Perform AU detection and HOG feature extraction, as this can be expensive only compute it if needed by output or visualization
if (recording_params.outputAlignedFaces() || recording_params.outputHOG() || recording_params.outputAUs() || visualizer.vis_align || visualizer.vis_hog)
{
face_analyser.PredictStaticAUs(captured_image, face_model.detected_landmarks);
face_analyser.PredictStaticAUsAndComputeFeatures(captured_image, face_model.detected_landmarks);
face_analyser.GetLatestAlignedFace(sim_warped_img);
face_analyser.GetLatestHOG(hog_descriptor, num_hog_rows, num_hog_cols);
}
@ -271,11 +271,12 @@ int main (int argc, char **argv)
open_face_rec.SetObservationFaceAlign(sim_warped_img);
open_face_rec.WriteObservation();
// Grabbing the next frame in the sequence
captured_image = image_reader.GetNextImage();
}
visualizer.ShowObservation();
// Grabbing the next frame in the sequence
captured_image = image_reader.GetNextImage();
}
return 0;

5
lib/local/FaceAnalyser/include/FaceAnalyser.h
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@ -73,9 +73,8 @@ public:
std::vector<std::pair<std::string, double>> GetCurrentAUsReg() const; // AU intensity
std::vector<std::pair<std::string, double>> GetCurrentAUsCombined() const; // Both presense and intensity
// A standalone call for predicting AUs from a static image, the first element in the pair represents occurence the second intensity
// This call is useful for detecting action units in images
std::pair<std::vector<std::pair<std::string, double>>, std::vector<std::pair<std::string, double>>> PredictStaticAUs(const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks);
// A standalone call for predicting AUs and computing face texture features from a static image
void PredictStaticAUsAndComputeFeatures(const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks);
void Reset();

14
lib/local/FaceAnalyser/src/FaceAnalyser.cpp
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@ -248,7 +248,7 @@ int GetViewId(const vector<cv::Vec3d> orientations_all, const cv::Vec3d& orienta
}
std::pair<std::vector<std::pair<string, double>>, std::vector<std::pair<string, double>>> FaceAnalyser::PredictStaticAUs(const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks)
void FaceAnalyser::PredictStaticAUsAndComputeFeatures(const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks)
{
// Extract shape parameters from the detected landmarks
@ -259,6 +259,16 @@ std::pair<std::vector<std::pair<string, double>>, std::vector<std::pair<string,
// First align the face
AlignFaceMask(aligned_face_for_au, frame, detected_landmarks, params_global, pdm, triangulation, true, 0.7, 112, 112);
// If the output requirement matches use the already computed one, else compute it again
if (align_scale_out == align_scale_au && align_width_out == align_width_au && align_height_out == align_height_au)
{
aligned_face_for_output = aligned_face_for_au.clone();
}
else
{
AlignFaceMask(aligned_face_for_output, frame, detected_landmarks, params_global, pdm, triangulation, true, align_scale_out, align_width_out, align_height_out);
}
// Extract HOG descriptor from the frame and convert it to a useable format
cv::Mat_<double> hog_descriptor;
Extract_FHOG_descriptor(hog_descriptor, aligned_face_for_au, this->num_hog_rows, this->num_hog_cols);
@ -303,8 +313,6 @@ std::pair<std::vector<std::pair<string, double>>, std::vector<std::pair<string,
AU_predictions_reg = AU_predictions_intensity;
AU_predictions_class = AU_predictions_occurence;
return std::pair<std::vector<std::pair<std::string, double>>, std::vector<std::pair<std::string, double>>>(AU_predictions_intensity, AU_predictions_occurence);
}
void FaceAnalyser::AddNextFrame(const cv::Mat& frame, const cv::Mat_<float>& detected_landmarks, bool success, double timestamp_seconds, bool online)

27
lib/local/Utilities/src/Visualizer.cpp
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@ -82,6 +82,7 @@ Visualizer::Visualizer(bool vis_track, bool vis_hog, bool vis_align)
this->vis_align = vis_align;
}
// Setting the image on which to draw
void Visualizer::SetImage(const cv::Mat& canvas, float fx, float fy, float cx, float cy)
{
captured_image = canvas.clone();
@ -89,20 +90,42 @@ void Visualizer::SetImage(const cv::Mat& canvas, float fx, float fy, float cx, f
this->fy = fy;
this->cx = cx;
this->cy = cy;
// Clearing other images
hog_image = cv::Mat();
aligned_face_image = cv::Mat();
}
void Visualizer::SetObservationFaceAlign(const cv::Mat& aligned_face)
{
this->aligned_face_image = aligned_face;
if(this->aligned_face_image.empty())
{
this->aligned_face_image = aligned_face;
}
else
{
cv::vconcat(this->aligned_face_image, aligned_face, this->aligned_face_image);
}
}
void Visualizer::SetObservationHOG(const cv::Mat_<double>& hog_descriptor, int num_cols, int num_rows)
{
if(vis_hog)
{
Visualise_FHOG(hog_descriptor, num_rows, num_cols, this->hog_image);
if (this->hog_image.empty())
{
Visualise_FHOG(hog_descriptor, num_rows, num_cols, this->hog_image);
}
else
{
cv::Mat tmp_hog;
Visualise_FHOG(hog_descriptor, num_rows, num_cols, tmp_hog);
cv::vconcat(this->hog_image, tmp_hog, this->hog_image);
}
}
}