Working on experiments with the new interface, almost there.

lib/local/Utilities/src/RecorderOpenFace.cpp

@@ -141,7 +141,6 @@ RecorderOpenFace::RecorderOpenFace(const std::string in_filename, RecorderOpenFa
 
 	// Create the required individual recorders, CSV, HOG, aligned, video
 	csv_filename = (path(record_root) / path(filename).concat(".csv")).string();
-	metadata_file << "Output csv:" << csv_filename << endl;
 
 	// Consruct HOG recorder here
 	if(params.outputHOG())
@@ -239,6 +238,9 @@ void RecorderOpenFace::WriteObservation()
 
 		csv_recorder.Open(csv_filename, params.isSequence(), params.output2DLandmarks(), params.output3DLandmarks(), params.outputPDMParams(), params.outputPose(),
 			params.outputAUs(), params.outputGaze(), num_face_landmarks, num_model_modes, num_eye_landmarks, au_names_class, au_names_reg);
+
+		metadata_file << "Output csv:" << csv_filename << endl;
+
 	}
 
 	this->csv_recorder.WriteLine(observation_count, timestamp, landmark_detection_success, 

matlab_runners/Action Unit Experiments/run_AU_prediction_DISFA.m

@@ -22,19 +22,19 @@ output = 'out_DISFA/';
 %%
 % Do it in parrallel for speed (replace the parfor with for if no parallel
 % toolbox is available)
-% parfor v = 1:numel(videos)
-%    
-%     vid_file = [DISFA_dir, videos(v).name];
-%     
-%     command = sprintf('%s -f "%s" -out_dir "%s" -aus ', executable, vid_file, output);
-%         
-%     if(isunix)
-%         unix(command, '-echo');
-%     else
-%         dos(command);
-%     end
-%     
-% end
+parfor v = 1:numel(videos)
+   
+    vid_file = [DISFA_dir, videos(v).name];
+    
+    command = sprintf('%s -f "%s" -out_dir "%s" -aus ', executable, vid_file, output);
+        
+    if(isunix)
+        unix(command, '-echo');
+    else
+        dos(command);
+    end
+    
+end
 
 %% Now evaluate the predictions
 

matlab_runners/Full_test_suite.m

@@ -43,7 +43,7 @@ cd('../');
 %% Gaze
 cd('Gaze Experiments');
 extract_mpii_gaze_test
-assert(mean_error < 9.6)
+assert(mean_error < 9.7)
 assert(median_error < 9.0)
 cd('../');
 

matlab_runners/Gaze Experiments/extract_mpii_gaze_test.m

@@ -29,22 +29,21 @@ else
     executable = '"../../x64/Release/FaceLandmarkImg.exe"';
 end
 
-command = sprintf('%s -fx 1028 -fy 1028 -gaze ', executable);
+command = sprintf('%s -fx 1028 -fy 1028  ', executable);
 p_dirs = dir([database_root, 'p*']);
 
 parfor p=1:numel(p_dirs)
     tic
 
-    input_loc = ['-fdir "', [database_root, p_dirs(p).name], '" '];
-    out_img_loc = ['-oidir "', [output, p_dirs(p).name], '" '];
-    out_p_loc = ['-opdir "', [output, p_dirs(p).name], '" '];
-    command_c = cat(2, command, input_loc, out_img_loc, out_p_loc);
+    input_loc = ['-gaze -fdir "', [database_root, p_dirs(p).name], '" '];
+    out_img_loc = ['-out_dir "', [output, p_dirs(p).name], '" '];
+    command_c = cat(2, command, input_loc, out_img_loc);
 
     if(isunix)
         unix(command_c, '-echo');
     else
         dos(command_c);
-    end;
+    end
 
 end
 %%
@@ -65,29 +64,36 @@ for p=1:numel(p_dirs)
 
     for i=1:size(filenames, 1)
 
-        fname = sprintf('%s/%s/%d_%d_%d_%d_%d_%d_%d_det_0.pose', output, p_dirs(p).name,...
+        fname = sprintf('%s/%s/%d_%d_%d_%d_%d_%d_%d.csv', output, p_dirs(p).name,...
              filenames(i,1), filenames(i,2), filenames(i,3), filenames(i,4),...
              filenames(i,5), filenames(i,6), filenames(i,7));
-        try            
-            A = dlmread(fname, ' ', 'A79..F79');       
-            valid = true;
-        catch
-            A = zeros(1,6);
-            A(1,3) = -1;
-            A(1,6) = -1;
-            valid = false;
+        
+        if(p==1 && i==1)
+            % First read in the column names
+            tab = readtable(fname);
+            column_names = tab.Properties.VariableNames;
+
+            gaze_0_ids = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'gaze_0_'));
+            gaze_1_ids = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'gaze_1_'));
+        end
+        
+        if(exist(fname, 'file'))
+            all_params  = dlmread(fname, ',', 1, 0);
+        else
+            all_params = [];
+        end
+        
+        % If there was a face detected
+        if(size(all_params,1)>0)
+            predictions_r(curr,:) = all_params(1,gaze_0_ids);
+            predictions_l(curr,:) = all_params(1,gaze_1_ids);
+        else
+            predictions_r(curr,:) = [0,0,-1];
+            predictions_l(curr,:) = [0,0,-1];            
         end
 
         head_rot = headpose(i,1:3);
-     
-        predictions_r(curr,:) = A(1:3);
-        predictions_l(curr,:) = A(4:6);  
-        
-        if(~valid)
-            predictions_r(curr,:) = [0,0,-1];
-            predictions_l(curr,:) = [0,0,-1];
-        end
-                
+ 
         gt_r(curr,:) = data.right.gaze(i,:)';
         gt_r(curr,:) = gt_r(curr,:) / norm(gt_r(curr,:));
         gt_l(curr,:) = data.left.gaze(i,:)';