More model simplification, getting there with img.
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2 changed files with 20 additions and 181 deletions
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@ -138,7 +138,7 @@ void create_display_image(const cv::Mat& orig, cv::Mat& display_image, LandmarkD
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}
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}
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LandmarkDetector::Draw(display_image, clnf_model);
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//LandmarkDetector::Draw(display_image, clnf_model);
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}
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}
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@ -176,7 +176,6 @@ int main (int argc, char **argv)
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face_analysis_params.OptimizeForImages();
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face_analysis_params.OptimizeForImages();
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FaceAnalysis::FaceAnalyser face_analyser(face_analysis_params);
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FaceAnalysis::FaceAnalyser face_analyser(face_analysis_params);
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// If bounding boxes not provided, use a face detector
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// If bounding boxes not provided, use a face detector
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cv::CascadeClassifier classifier(det_parameters.face_detector_location);
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cv::CascadeClassifier classifier(det_parameters.face_detector_location);
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dlib::frontal_face_detector face_detector_hog = dlib::get_frontal_face_detector();
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dlib::frontal_face_detector face_detector_hog = dlib::get_frontal_face_detector();
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@ -195,13 +194,15 @@ int main (int argc, char **argv)
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// Making sure the image is in uchar grayscale
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// Making sure the image is in uchar grayscale
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cv::Mat_<uchar> grayscale_image = image_reader.GetGrayFrame();
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cv::Mat_<uchar> grayscale_image = image_reader.GetGrayFrame();
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// if no pose defined we just use a face detector
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if(bounding_boxes.empty())
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{
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// Detect faces in an image
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// Detect faces in an image
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vector<cv::Rect_<double> > face_detections;
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vector<cv::Rect_<double> > face_detections;
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if (image_reader.has_bounding_boxes)
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{
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face_detections = image_reader.GetBoundingBoxes();
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}
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else
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{
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if (det_parameters.curr_face_detector == LandmarkDetector::FaceModelParameters::HOG_SVM_DETECTOR)
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if (det_parameters.curr_face_detector == LandmarkDetector::FaceModelParameters::HOG_SVM_DETECTOR)
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{
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{
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vector<double> confidences;
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vector<double> confidences;
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@ -211,6 +212,7 @@ int main (int argc, char **argv)
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{
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{
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LandmarkDetector::DetectFaces(face_detections, grayscale_image, classifier);
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LandmarkDetector::DetectFaces(face_detections, grayscale_image, classifier);
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}
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}
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}
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// Detect landmarks around detected faces
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// Detect landmarks around detected faces
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int face_det = 0;
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int face_det = 0;
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@ -218,10 +220,10 @@ int main (int argc, char **argv)
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for (size_t face = 0; face < face_detections.size(); ++face)
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for (size_t face = 0; face < face_detections.size(); ++face)
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{
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{
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// if there are multiple detections go through them
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// if there are multiple detections go through them
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bool success = LandmarkDetector::DetectLandmarksInImage(grayscale_image, face_detections[face], clnf_model, det_parameters);
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bool success = LandmarkDetector::DetectLandmarksInImage(grayscale_image, face_detections[face], face_model, det_parameters);
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// Estimate head pose and eye gaze
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// Estimate head pose and eye gaze
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cv::Vec6d headPose = LandmarkDetector::GetPose(clnf_model, fx, fy, cx, cy);
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cv::Vec6d headPose = LandmarkDetector::GetPose(face_model, image_reader.fx, image_reader.fy, image_reader.cx, image_reader.cy);
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// Gaze tracking, absolute gaze direction
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// Gaze tracking, absolute gaze direction
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cv::Point3f gazeDirection0(0, 0, -1);
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cv::Point3f gazeDirection0(0, 0, -1);
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@ -230,179 +232,16 @@ int main (int argc, char **argv)
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if (success && det_parameters.track_gaze)
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if (success && det_parameters.track_gaze)
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{
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{
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GazeAnalysis::EstimateGaze(clnf_model, gazeDirection0, fx, fy, cx, cy, true);
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GazeAnalysis::EstimateGaze(face_model, gazeDirection0, image_reader.fx, image_reader.fy, image_reader.cx, image_reader.cy, true);
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GazeAnalysis::EstimateGaze(clnf_model, gazeDirection1, fx, fy, cx, cy, false);
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GazeAnalysis::EstimateGaze(face_model, gazeDirection1, image_reader.fx, image_reader.fy, image_reader.cx, image_reader.cy, false);
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gazeAngle = GazeAnalysis::GetGazeAngle(gazeDirection0, gazeDirection1);
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gazeAngle = GazeAnalysis::GetGazeAngle(gazeDirection0, gazeDirection1);
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}
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}
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auto ActionUnits = face_analyser.PredictStaticAUs(read_image, clnf_model.detected_landmarks, false);
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auto ActionUnits = face_analyser.PredictStaticAUs(captured_image, face_model.detected_landmarks);
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// Writing out the detected landmarks (in an OS independent manner)
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// TODO visualize
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if(!output_landmark_locations.empty())
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{
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char name[100];
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// append detection number (in case multiple faces are detected)
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sprintf(name, "_det_%d", face_det);
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// Construct the output filename
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// TODO record
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boost::filesystem::path slash("/");
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std::string preferredSlash = slash.make_preferred().string();
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boost::filesystem::path out_feat_path(output_landmark_locations.at(i));
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boost::filesystem::path dir = out_feat_path.parent_path();
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boost::filesystem::path fname = out_feat_path.filename().replace_extension("");
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boost::filesystem::path ext = out_feat_path.extension();
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string outfeatures = dir.string() + preferredSlash + fname.string() + string(name) + ext.string();
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write_out_landmarks(outfeatures, clnf_model, headPose, gazeDirection0, gazeDirection1, gazeAngle, ActionUnits.first, ActionUnits.second, det_parameters.track_gaze);
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}
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if (!output_pose_locations.empty())
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{
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char name[100];
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// append detection number (in case multiple faces are detected)
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sprintf(name, "_det_%d", face_det);
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// Construct the output filename
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boost::filesystem::path slash("/");
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std::string preferredSlash = slash.make_preferred().string();
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boost::filesystem::path out_pose_path(output_pose_locations.at(i));
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boost::filesystem::path dir = out_pose_path.parent_path();
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boost::filesystem::path fname = out_pose_path.filename().replace_extension("");
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boost::filesystem::path ext = out_pose_path.extension();
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string outfeatures = dir.string() + preferredSlash + fname.string() + string(name) + ext.string();
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write_out_pose_landmarks(outfeatures, clnf_model.GetShape(fx, fy, cx, cy), headPose, gazeDirection0, gazeDirection1);
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}
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if (det_parameters.track_gaze)
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{
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cv::Vec6d pose_estimate_to_draw = LandmarkDetector::GetPose(clnf_model, fx, fy, cx, cy);
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// Draw it in reddish if uncertain, blueish if certain
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LandmarkDetector::DrawBox(read_image, pose_estimate_to_draw, cv::Scalar(255.0, 0, 0), 3, fx, fy, cx, cy);
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GazeAnalysis::DrawGaze(read_image, clnf_model, gazeDirection0, gazeDirection1, fx, fy, cx, cy);
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}
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// displaying detected landmarks
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cv::Mat display_image;
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create_display_image(read_image, display_image, clnf_model);
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if(visualise && success)
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{
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imshow("colour", display_image);
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cv::waitKey(1);
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}
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// Saving the display images (in an OS independent manner)
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if(!output_images.empty() && success)
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{
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string outimage = output_images.at(i);
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if(!outimage.empty())
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{
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char name[100];
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sprintf(name, "_det_%d", face_det);
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boost::filesystem::path slash("/");
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std::string preferredSlash = slash.make_preferred().string();
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// append detection number
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boost::filesystem::path out_feat_path(outimage);
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boost::filesystem::path dir = out_feat_path.parent_path();
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boost::filesystem::path fname = out_feat_path.filename().replace_extension("");
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boost::filesystem::path ext = out_feat_path.extension();
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outimage = dir.string() + preferredSlash + fname.string() + string(name) + ext.string();
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create_directory_from_file(outimage);
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bool write_success = cv::imwrite(outimage, display_image);
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if (!write_success)
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{
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cout << "Could not output a processed image" << endl;
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return 1;
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}
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}
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}
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if(success)
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{
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face_det++;
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}
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}
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}
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else
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{
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// Have provided bounding boxes
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LandmarkDetector::DetectLandmarksInImage(grayscale_image, bounding_boxes[i], clnf_model, det_parameters);
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// Estimate head pose and eye gaze
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cv::Vec6d headPose = LandmarkDetector::GetPose(clnf_model, fx, fy, cx, cy);
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// Gaze tracking, absolute gaze direction
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cv::Point3f gazeDirection0(0, 0, -1);
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cv::Point3f gazeDirection1(0, 0, -1);
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cv::Vec2d gazeAngle(0, 0);
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if (det_parameters.track_gaze)
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{
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GazeAnalysis::EstimateGaze(clnf_model, gazeDirection0, fx, fy, cx, cy, true);
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GazeAnalysis::EstimateGaze(clnf_model, gazeDirection1, fx, fy, cx, cy, false);
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gazeAngle = GazeAnalysis::GetGazeAngle(gazeDirection0, gazeDirection1);
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}
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auto ActionUnits = face_analyser.PredictStaticAUs(read_image, clnf_model.detected_landmarks, false);
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// Writing out the detected landmarks
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if(!output_landmark_locations.empty())
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{
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string outfeatures = output_landmark_locations.at(i);
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write_out_landmarks(outfeatures, clnf_model, headPose, gazeDirection0, gazeDirection1, gazeAngle, ActionUnits.first, ActionUnits.second, det_parameters.track_gaze);
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}
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// Writing out the detected landmarks
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if (!output_pose_locations.empty())
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{
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string outfeatures = output_pose_locations.at(i);
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write_out_pose_landmarks(outfeatures, clnf_model.GetShape(fx, fy, cx, cy), headPose, gazeDirection0, gazeDirection1);
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}
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// displaying detected stuff
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cv::Mat display_image;
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if (det_parameters.track_gaze)
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{
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cv::Vec6d pose_estimate_to_draw = LandmarkDetector::GetPose(clnf_model, fx, fy, cx, cy);
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// Draw it in reddish if uncertain, blueish if certain
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LandmarkDetector::DrawBox(read_image, pose_estimate_to_draw, cv::Scalar(255.0, 0, 0), 3, fx, fy, cx, cy);
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GazeAnalysis::DrawGaze(read_image, clnf_model, gazeDirection0, gazeDirection1, fx, fy, cx, cy);
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}
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create_display_image(read_image, display_image, clnf_model);
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if(visualise)
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{
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imshow("colour", display_image);
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cv::waitKey(1);
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}
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if(!output_images.empty())
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{
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string outimage = output_images.at(i);
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if(!outimage.empty())
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{
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create_directory_from_file(outimage);
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bool write_success = imwrite(outimage, display_image);
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if (!write_success)
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{
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cout << "Could not output a processed image" << endl;
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return 1;
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}
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}
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}
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}
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}
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}
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}
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