open source pkg v1

2020-08-04 19:12:31 -04:00
parent bef213dba9
commit c389fc2c47
3708 changed files with 1624220 additions and 1 deletions
--- a/pkg/OpenFace/matlab_runners/Head
+++ b/pkg/OpenFace/matlab_runners/Head
@@ -0,0 +1,101 @@
+function [meanError, all_rot_preds, all_rot_gts, meanErrors, all_errors, rels_all, seq_ids] = calcBiwiError(resDir, gtDir)
+
+seqNames = {'01','02','03','04','05','06','07','08','09', ...
+    '10', '11','12','13','14','15','16','17','18','19', ...
+    '20', '21','22','23','24'};
+
+rotMeanErr = zeros(numel(seqNames),3);
+rotRMS = zeros(numel(seqNames),3);
+rot = cell(1,numel(seqNames));
+rotg = cell(1,numel(seqNames));
+rels_all = [];
+
+seq_ids = {};
+
+for i=1:numel(seqNames)
+        
+    posesGround =  load ([gtDir '/' seqNames{i} '/groundTruthPose.txt']);
+     
+    fname = [resDir seqNames{i} '.csv'];
+    if(i == 1)
+        % First read in the column names
+        tab = readtable(fname);
+        column_names = tab.Properties.VariableNames;
+
+        confidence_id = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'confidence'));
+        rot_ids = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'pose_R'));
+        t_ids = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'pose_T'));
+    end
+
+    all_params  = dlmread(fname, ',', 1, 0);
+    
+    T = all_params(:,t_ids);
+    tx = T(:,1);    
+    ty = T(:,2);
+    tz = T(:,3);
+
+    rot{i} = all_params(:, rot_ids);    
+    rels = all_params(:, confidence_id);
+    
+    % the reliabilities of head pose
+    rels_all = cat(1, rels_all, rels);    
+    
+    rotg{i} = posesGround(:,[5 6 7]);
+    
+    % Correct the first frame so it corresponds to (0,0,0), as slightly
+    % different pose might be assumed frontal and this corrects for
+    % that
+    
+    % Work out the correction matrix for ground truth
+    rot_corr_gt = Euler2Rot(rotg{i}(1,:));
+    for r_e = 1:size(rotg{i},1)
+        rot_curr_gt = Euler2Rot(rotg{i}(r_e,:));
+        rot_new_gt = rot_corr_gt' * rot_curr_gt;
+        rotg{i}(r_e,:) = Rot2Euler(rot_new_gt);
+    end
+    
+    % First move the orientation to camera space
+    zx = sqrt(tx.^2 + tz.^2);
+    eul_x = atan2(ty, zx);
+    
+    zy = sqrt(ty.^2 + tz.^2);
+    eul_y = -atan2(tx, zy);
+    for r_e = 1:size(rot{i},1)
+        cam_rot = Euler2Rot([eul_x(r_e), eul_y(r_e), 0]);
+        h_rot = Euler2Rot(rot{i}(r_e,:));
+
+        c_rot = cam_rot * h_rot;
+        rot{i}(r_e,:) = Rot2Euler(c_rot);
+    end
+    
+    % Work out the correction matrix for estimates        
+    rot_corr_est = Euler2Rot(rot{i}(1,:));
+    for r_e = 1:size(rot{i},1)
+        rot_curr_est = Euler2Rot(rot{i}(r_e,:));
+        rot_new_est = rot_corr_est' * rot_curr_est;
+        rot{i}(r_e,:) = Rot2Euler(rot_new_est);
+    end
+    
+    rotg{i} = rotg{i} * 180 / pi;
+    rot{i} = rot{i} * 180 / pi;  
+
+    
+    rotMeanErr(i,:) = mean(abs((rot{i}(:,:)-rotg{i}(:,:))));
+    rotRMS(i,:) = sqrt(mean(((rot{i}(:,:)-rotg{i}(:,:))).^2)); 
+    
+    seq_ids = cat(1, seq_ids, repmat(seqNames(i), size(rot{i},1), 1));
+    
+end
+%%
+meanErrors = rotMeanErr;
+allRot = cell2mat(rot');
+allRotg = cell2mat(rotg');
+meanError = mean(abs((allRot(:,:)-allRotg(:,:))));
+
+all_errors = abs(allRot-allRotg);
+
+rmsError = sqrt(mean(((allRot(:,:)-allRotg(:,:))).^2)); 
+errorVariance = std(abs((allRot(:,:)-allRotg(:,:))));
+
+all_rot_preds = allRot;
+all_rot_gts = allRotg;