open source pkg v1

pkg/OpenFace/matlab_version/experiments_300W/Collect_wild_imgs.m

@@ -0,0 +1,226 @@
+function [images, detections, labels] = Collect_wild_imgs(root_test_data)
+       
+    use_afw = true;
+    use_lfpw = true;
+    use_helen = true;
+    use_ibug = true;
+    
+    use_68 = true;           
+    
+    images = [];
+    labels = [];
+    detections = [];
+    
+    if(use_afw)
+        [img, det, lbl] = Collect_AFW(root_test_data, use_68);
+        images = cat(1, images, img');
+        detections = cat(1, detections, det);
+        labels = cat(1, labels, lbl);        
+    end
+    
+    if(use_lfpw)
+        [img, det, lbl] = Collect_LFPW(root_test_data, use_68);
+        images = cat(1, images, img');
+        detections = cat(1, detections, det);
+        labels = cat(1, labels, lbl);        
+    end    
+    
+    if(use_ibug)
+        [img, det, lbl] = Collect_ibug(root_test_data, use_68);
+        images = cat(1, images, img');
+        detections = cat(1, detections, det);
+        labels = cat(1, labels, lbl);        
+    end
+    
+    if(use_helen)
+        [img, det, lbl] = Collect_helen(root_test_data, use_68);
+        images = cat(1, images, img');
+        detections = cat(1, detections, det);
+        labels = cat(1, labels, lbl);        
+    end    
+
+    % convert to format expected by the Fitting method
+    detections(:,3) = detections(:,1) + detections(:,3);
+    detections(:,4) = detections(:,2) + detections(:,4);
+    
+
+end
+
+
+function [images, detections, labels] = Collect_AFW(root_test_data, use_68)
+    
+dataset_loc = [root_test_data, '/AFW/'];
+
+landmarkLabels = dir([dataset_loc '\*.pts']);
+
+num_imgs = size(landmarkLabels,1);
+
+images = struct;
+if(use_68)
+    labels = zeros(num_imgs, 68, 2);    
+else
+    labels = zeros(num_imgs, 66, 2);
+end
+
+detections = zeros(num_imgs, 4);
+
+load([root_test_data, '/Bounding Boxes/bounding_boxes_afw.mat']);
+num_landmarks = 68;
+
+for imgs = 1:num_imgs
+
+    [~,name,~] = fileparts(landmarkLabels(imgs).name);
+        
+    landmarks = dlmread([dataset_loc, landmarkLabels(imgs).name], ' ', [3,0,num_landmarks+2,1]);
+    
+    if(~use_68)
+        inds_frontal = [1:60,62:64,66:68];
+        landmarks = landmarks(inds_frontal,:);
+    end
+    
+    images(imgs).img = [dataset_loc,  name '.jpg'];
+    labels(imgs,:,:) = landmarks;
+                   
+    detections(imgs,:) = bounding_boxes{imgs}.bb_detector;
+    
+end
+
+detections(:,3) = detections(:,3) - detections(:,1);
+detections(:,4) = detections(:,4) - detections(:,2);
+
+end
+
+function [images, detections, labels] = Collect_LFPW(root_test_data, use_68)
+    
+dataset_loc = [root_test_data, '/lfpw/testset/'];
+
+landmarkLabels = dir([dataset_loc '\*.pts']);
+
+num_imgs = size(landmarkLabels,1);
+
+images = struct;
+if(use_68)
+    labels = zeros(num_imgs, 68, 2);    
+else
+    labels = zeros(num_imgs, 66, 2);
+end
+
+detections = zeros(num_imgs, 4);
+
+load([root_test_data, '/Bounding Boxes/bounding_boxes_lfpw_testset.mat']);
+
+num_landmarks = 68;
+
+for imgs = 1:num_imgs
+
+    [~,name,~] = fileparts(landmarkLabels(imgs).name);
+        
+    landmarks = dlmread([dataset_loc, landmarkLabels(imgs).name], ' ', [3,0,num_landmarks+2,1]);
+
+    if(~use_68)
+        inds_frontal = [1:60,62:64,66:68];
+        landmarks = landmarks(inds_frontal,:);
+    end
+    
+    images(imgs).img = [dataset_loc,  name '.png'];
+    
+    labels(imgs,:,:) = landmarks;
+    
+    detections(imgs,:) = bounding_boxes{imgs}.bb_detector;
+    
+end
+
+detections(:,3) = detections(:,3) - detections(:,1);
+detections(:,4) = detections(:,4) - detections(:,2);
+
+
+end
+
+function [images, detections, labels] = Collect_ibug(root_test_data, use_68)
+    
+dataset_loc = [root_test_data, '/ibug/'];
+
+landmarkLabels = dir([dataset_loc '\*.pts']);
+
+num_imgs = size(landmarkLabels,1);
+
+images = struct;
+
+if(use_68)
+    labels = zeros(num_imgs, 68, 2);    
+else
+    labels = zeros(num_imgs, 66, 2);
+end
+
+detections = zeros(num_imgs, 4);
+
+load([root_test_data, '/Bounding Boxes/bounding_boxes_ibug.mat']);
+num_landmarks = 68;
+
+for imgs = 1:num_imgs
+
+    [~,name,~] = fileparts(landmarkLabels(imgs).name);
+        
+    landmarks = dlmread([dataset_loc, landmarkLabels(imgs).name], ' ', [3,0,num_landmarks+2,1]);
+
+    if(~use_68)
+        inds_frontal = [1:60,62:64,66:68];
+        landmarks = landmarks(inds_frontal,:);
+    end
+    
+    images(imgs).img = [dataset_loc,  name '.jpg'];
+    
+    labels(imgs,:,:) = landmarks;
+    
+    detections(imgs,:) = bounding_boxes{imgs}.bb_detector;
+    
+end
+
+detections(:,3) = detections(:,3) - detections(:,1);
+detections(:,4) = detections(:,4) - detections(:,2);
+
+end
+
+function [images, detections, labels] = Collect_helen(root_test_data, use_68)
+    
+dataset_loc = [root_test_data, '/helen/testset/'];
+
+landmarkLabels = dir([dataset_loc '\*.pts']);
+
+num_imgs = size(landmarkLabels,1);
+
+images = struct;
+
+if(use_68)
+    labels = zeros(num_imgs, 68, 2);    
+else
+    labels = zeros(num_imgs, 66, 2);
+end
+
+detections = zeros(num_imgs, 4);
+
+load([root_test_data, '/Bounding Boxes/bounding_boxes_helen_testset.mat']);
+num_landmarks = 68;
+for imgs = 1:num_imgs
+
+    [~,name,~] = fileparts(landmarkLabels(imgs).name);
+    
+    landmarks = dlmread([dataset_loc, landmarkLabels(imgs).name], ' ', [3,0,num_landmarks+2,1]);
+    
+    if(~use_68)
+        inds_frontal = [1:60,62:64,66:68];
+        landmarks = landmarks(inds_frontal,:);
+    end
+    
+    images(imgs).img = [dataset_loc,  name '.jpg'];
+    
+    labels(imgs,:,:) = landmarks;
+    
+    detections(imgs,:) = bounding_boxes{imgs}.bb_detector;
+    
+end
+
+detections(:,3) = detections(:,3) - detections(:,1);
+detections(:,4) = detections(:,4) - detections(:,2);
+
+end

pkg/OpenFace/matlab_version/experiments_300W/Construct_error_table.m

@@ -0,0 +1,35 @@
+% Run this in order to construct the results table for the CE-CLM paper
+Extract_table_results_68;
+
+file_out = fopen('results/300W_68.txt', 'w');
+
+fprintf(file_out, 'Errors with outline (68 points)\n');
+fprintf(file_out, '------------------------------\n');
+fprintf(file_out, 'Method\tcomm\tdiff\n');
+fprintf(file_out, 'CLNF\t%.2f\t%.2f\n', median(clnf_error_comm)*100, median(clnf_error_ibug)*100);
+fprintf(file_out, 'CFAN\t--- \t%.2f\n', median(cfan_error_ibug)*100);
+fprintf(file_out, 'DRMF\t%.2f\t%.2f\n', median(drmf_error_comm)*100, median(drmf_error_ibug)*100);
+fprintf(file_out, 'CFSS\t%.2f\t%.2f\n', median(cfss_error_comm)*100, median(cfss_error_ibug)*100);
+fprintf(file_out, 'TCDCN\t%.2f\t%.2f\n', median(tcdcn_error_comm)*100, median(tcdcn_error_ibug)*100);
+fprintf(file_out, '3DDFA\t%.2f\t%.2f\n', median(error_3ddfa_comm)*100, median(error_3ddfa_ibug)*100);
+fprintf(file_out, '------------------------------\n');
+fprintf(file_out, 'CE-CLM\t%.2f\t%.2f\n', median(ceclm_error_comm)*100, median(ceclm_error_ibug)*100);
+fclose(file_out);
+
+Extract_table_results_49;
+file_out = fopen('results/300W_49.txt', 'w');
+
+fprintf(file_out, 'Errors without outline (49 points)\n');
+fprintf(file_out, '------------------------------\n');
+fprintf(file_out, 'Method\tcomm\tdiff\n');
+fprintf(file_out, 'CLNF\t%.2f\t%.2f\n', median(clnf_error_comm)*100, median(clnf_error_ibug)*100);
+fprintf(file_out, 'SDM \t%.2f\t%.2f\n', median(sdm_error_comm)*100, median(sdm_error_ibug)*100);
+fprintf(file_out, 'CFAN\t--- \t%.2f\n', median(cfan_error_ibug)*100);
+fprintf(file_out, 'DRMF\t%.2f\t%.2f\n', median(drmf_error_comm)*100, median(drmf_error_ibug)*100);
+fprintf(file_out, 'CFSS\t%.2f\t%.2f\n', median(cfss_error_comm)*100, median(cfss_error_ibug)*100);
+fprintf(file_out, 'TCDCN\t%.2f\t%.2f\n', median(tcdcn_error_comm)*100, median(tcdcn_error_ibug)*100);
+fprintf(file_out, '3DDFA\t%.2f\t%.2f\n', median(error_3ddfa_comm)*100, median(error_3ddfa_ibug)*100);
+fprintf(file_out, '------------------------------\n');
+fprintf(file_out, 'CE-CLM\t%.2f\t%.2f\n', median(ceclm_error_comm)*100, median(ceclm_error_ibug)*100);
+
+fclose(file_out);

pkg/OpenFace/matlab_version/experiments_300W/Display_ceclm_results_49.m

@@ -0,0 +1,160 @@
+clear
+close all
+
+% First grab the numbers
+Extract_table_results_49;
+
+%% Visualize all the baselines on all 300W
+scrsz = get(0,'ScreenSize');
+figure1 = figure('Position',[20 50 3*scrsz(3)/4 0.9*scrsz(4)]);
+
+set(figure1,'Units','Inches');
+pos = get(figure1,'Position');
+set(figure1,'PaperPositionMode','Auto','PaperUnits','Inches','PaperSize',[pos(3), pos(4)])
+
+% Create axes
+axes1 = axes('Parent',figure1,'FontSize',40,'FontName','Helvetica');
+
+line_width = 6;
+hold on;
+
+[error_x, error_y] = cummErrorCurve(cat(1, ceclm_error_comm, ceclm_error_ibug));
+plot(error_x, error_y, 'r', 'DisplayName', 'CE-CLM ', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cat(1, clnf_error_comm, clnf_error_ibug));
+plot(error_x, error_y, 'DisplayName', 'CLNF', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cat(1, error_3ddfa_comm, error_3ddfa_ibug));
+plot(error_x, error_y, 'DisplayName', '3DDFA', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cat(1, drmf_error_comm, drmf_error_ibug));
+plot(error_x, error_y, 'DisplayName', 'DRMF', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cat(1, cfss_error_comm, cfss_error_ibug));
+plot(error_x, error_y, 'DisplayName', 'CFSS', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cat(1, sdm_error_comm, sdm_error_ibug));
+plot(error_x, error_y, 'DisplayName', 'SDM', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cat(1, tcdcn_error_comm, tcdcn_error_ibug));
+plot(error_x, error_y, 'DisplayName', 'TCDCN', 'LineWidth',line_width);
+
+set(gca,'xtick',[0:0.01:0.1])
+xlim([0.01,0.07]);
+xlabel('IOD normalised MAE','FontName','Helvetica');
+ylabel('Proportion of images','FontName','Helvetica');
+grid on
+% title('Fitting in the wild without outline','FontSize',60,'FontName','Helvetica');
+
+leg = legend('show', 'Location', 'SouthEast');
+set(leg,'FontSize',50)
+
+% Make sure CE-CLM curve is on top
+[error_x, error_y] = cummErrorCurve(cat(1, ceclm_error_comm, ceclm_error_ibug));
+plot(error_x, error_y, 'r', 'LineWidth',line_width);
+
+print -dpdf results/ceclm-300W-49.pdf
+print -dpng results/ceclm-300W-49.png
+%% Visualize all the baselines on difficult subset of 300W
+scrsz = get(0,'ScreenSize');
+figure1 = figure('Position',[20 50 3*scrsz(3)/4 0.9*scrsz(4)]);
+
+set(figure1,'Units','Inches');
+pos = get(figure1,'Position');
+set(figure1,'PaperPositionMode','Auto','PaperUnits','Inches','PaperSize',[pos(3), pos(4)])
+
+% Create axes
+axes1 = axes('Parent',figure1,'FontSize',40,'FontName','Helvetica');
+
+line_width = 6;
+hold on;
+
+[error_x, error_y] = cummErrorCurve(ceclm_error_ibug);
+plot(error_x, error_y, 'r', 'DisplayName', 'CE-CLM ', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(clnf_error_ibug);
+plot(error_x, error_y, 'DisplayName', 'CLNF', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(error_3ddfa_ibug);
+plot(error_x, error_y, 'DisplayName', '3DDFA', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(drmf_error_ibug);
+plot(error_x, error_y, 'DisplayName', 'DRMF', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cfss_error_ibug);
+plot(error_x, error_y, 'DisplayName', 'CFSS', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(sdm_error_ibug);
+plot(error_x, error_y, 'DisplayName', 'SDM', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(tcdcn_error_ibug);
+plot(error_x, error_y, 'DisplayName', 'TCDCN', 'LineWidth',line_width);
+
+set(gca,'xtick',[0:0.01:0.1])
+xlim([0.02,0.09]);
+xlabel('IOD normalised MAE','FontName','Helvetica');
+ylabel('Proportion of images','FontName','Helvetica');
+grid on
+% title('Fitting in the wild without outline','FontSize',60,'FontName','Helvetica');
+
+leg = legend('show', 'Location', 'SouthEast');
+set(leg,'FontSize',50)
+
+% Make sure CE-CLM curve is on top
+[error_x, error_y] = cummErrorCurve(ceclm_error_ibug);
+plot(error_x, error_y, 'r', 'LineWidth',line_width);
+
+print -dpdf results/ceclm-300W-ibug-49.pdf
+print -dpng results/ceclm-300W-ibug-49.png
+
+%% Visualize all the baselines on difficult subset of 300W
+scrsz = get(0,'ScreenSize');
+figure1 = figure('Position',[20 50 3*scrsz(3)/4 0.9*scrsz(4)]);
+
+set(figure1,'Units','Inches');
+pos = get(figure1,'Position');
+set(figure1,'PaperPositionMode','Auto','PaperUnits','Inches','PaperSize',[pos(3), pos(4)])
+
+% Create axes
+axes1 = axes('Parent',figure1,'FontSize',40,'FontName','Helvetica');
+
+line_width = 6;
+hold on;
+
+[error_x, error_y] = cummErrorCurve(ceclm_error_comm);
+plot(error_x, error_y, 'r', 'DisplayName', 'CE-CLM ', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(clnf_error_comm);
+plot(error_x, error_y, 'DisplayName', 'CLNF', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(error_3ddfa_comm);
+plot(error_x, error_y, 'DisplayName', '3DDFA', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(drmf_error_comm);
+plot(error_x, error_y, 'DisplayName', 'DRMF', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cfss_error_comm);
+plot(error_x, error_y, 'DisplayName', 'CFSS', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(sdm_error_comm);
+plot(error_x, error_y, 'DisplayName', 'SDM', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(tcdcn_error_comm);
+plot(error_x, error_y, 'DisplayName', 'TCDCN', 'LineWidth',line_width);
+
+set(gca,'xtick',[0:0.01:0.1])
+xlim([0.01,0.07]);
+xlabel('IOD normalised MAE','FontName','Helvetica');
+ylabel('Proportion of images','FontName','Helvetica');
+grid on
+% title('Fitting in the wild without outline','FontSize',60,'FontName','Helvetica');
+
+leg = legend('show', 'Location', 'SouthEast');
+set(leg,'FontSize',50)
+
+% Make sure CE-CLM curve is on top
+[error_x, error_y] = cummErrorCurve(ceclm_error_comm);
+plot(error_x, error_y, 'r', 'LineWidth',line_width);
+
+print -dpdf results/ceclm-300W-comm-49.pdf
+print -dpng results/ceclm-300W-comm-49.png

pkg/OpenFace/matlab_version/experiments_300W/Display_ceclm_results_68.m

@@ -0,0 +1,150 @@
+clear
+
+% First grab the numbers
+Extract_table_results_68;
+
+%% Visualize all the baselines on all 300W
+scrsz = get(0,'ScreenSize');
+figure1 = figure('Position',[20 50 3*scrsz(3)/4 0.9*scrsz(4)]);
+
+set(figure1,'Units','Inches');
+pos = get(figure1,'Position');
+set(figure1,'PaperPositionMode','Auto','PaperUnits','Inches','PaperSize',[pos(3), pos(4)])
+
+% Create axes
+axes1 = axes('Parent',figure1,'FontSize',40,'FontName','Helvetica');
+
+line_width = 6;
+hold on;
+
+[error_x, error_y] = cummErrorCurve(cat(1, ceclm_error_comm, ceclm_error_ibug));
+plot(error_x, error_y, 'r', 'DisplayName', 'CE-CLM ', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cat(1, clnf_error_comm, clnf_error_ibug));
+plot(error_x, error_y, 'DisplayName', 'CLNF', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cat(1, error_3ddfa_comm, error_3ddfa_ibug));
+plot(error_x, error_y, 'DisplayName', '3DDFA', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cat(1, drmf_error_comm, drmf_error_ibug));
+plot(error_x, error_y, 'DisplayName', 'DRMF', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cat(1, cfss_error_comm, cfss_error_ibug));
+plot(error_x, error_y, 'DisplayName', 'CFSS', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cat(1, tcdcn_error_comm, tcdcn_error_ibug));
+plot(error_x, error_y, 'DisplayName', 'TCDCN', 'LineWidth',line_width);
+
+set(gca,'xtick',[0:0.01:0.1])
+xlim([0.01,0.07]);
+xlabel('IOD normalised MAE','FontName','Helvetica');
+ylabel('Proportion of images','FontName','Helvetica');
+grid on
+% title('Fitting in the wild without outline','FontSize',60,'FontName','Helvetica');
+
+leg = legend('show', 'Location', 'SouthEast');
+set(leg,'FontSize',50)
+
+% Make sure CE-CLM curve is on top
+[error_x, error_y] = cummErrorCurve(cat(1, ceclm_error_comm, ceclm_error_ibug));
+plot(error_x, error_y, 'r', 'LineWidth',line_width);
+
+print -dpdf results/ceclm-300W-68.pdf
+print -dpng results/ceclm-300W-68.png
+%% Visualize all the baselines on difficult subset of 300W
+scrsz = get(0,'ScreenSize');
+figure1 = figure('Position',[20 50 3*scrsz(3)/4 0.9*scrsz(4)]);
+
+set(figure1,'Units','Inches');
+pos = get(figure1,'Position');
+set(figure1,'PaperPositionMode','Auto','PaperUnits','Inches','PaperSize',[pos(3), pos(4)])
+
+% Create axes
+axes1 = axes('Parent',figure1,'FontSize',40,'FontName','Helvetica');
+
+line_width = 6;
+hold on;
+
+[error_x, error_y] = cummErrorCurve(ceclm_error_ibug);
+plot(error_x, error_y, 'r', 'DisplayName', 'CE-CLM ', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(clnf_error_ibug);
+plot(error_x, error_y, 'DisplayName', 'CLNF', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(error_3ddfa_ibug);
+plot(error_x, error_y, 'DisplayName', '3DDFA', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(drmf_error_ibug);
+plot(error_x, error_y, 'DisplayName', 'DRMF', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cfss_error_ibug);
+plot(error_x, error_y, 'DisplayName', 'CFSS', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(tcdcn_error_ibug);
+plot(error_x, error_y, 'DisplayName', 'TCDCN', 'LineWidth',line_width);
+
+set(gca,'xtick',[0:0.01:0.1])
+xlim([0.02,0.09]);
+xlabel('IOD normalised MAE','FontName','Helvetica');
+ylabel('Proportion of images','FontName','Helvetica');
+grid on
+% title('Fitting in the wild without outline','FontSize',60,'FontName','Helvetica');
+
+leg = legend('show', 'Location', 'SouthEast');
+set(leg,'FontSize',50)
+
+% Make sure CE-CLM curve is on top
+[error_x, error_y] = cummErrorCurve(ceclm_error_ibug);
+plot(error_x, error_y, 'r', 'LineWidth',line_width);
+
+print -dpdf results/ceclm-300W-ibug-68.pdf
+print -dpng results/ceclm-300W-ibug-68.png
+
+%% Visualize all the baselines on difficult subset of 300W
+scrsz = get(0,'ScreenSize');
+figure1 = figure('Position',[20 50 3*scrsz(3)/4 0.9*scrsz(4)]);
+
+set(figure1,'Units','Inches');
+pos = get(figure1,'Position');
+set(figure1,'PaperPositionMode','Auto','PaperUnits','Inches','PaperSize',[pos(3), pos(4)])
+
+% Create axes
+axes1 = axes('Parent',figure1,'FontSize',40,'FontName','Helvetica');
+
+line_width = 6;
+hold on;
+
+[error_x, error_y] = cummErrorCurve(ceclm_error_comm);
+plot(error_x, error_y, 'r', 'DisplayName', 'CE-CLM ', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(clnf_error_comm);
+plot(error_x, error_y, 'DisplayName', 'CLNF', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(error_3ddfa_comm);
+plot(error_x, error_y, 'DisplayName', '3DDFA', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(drmf_error_comm);
+plot(error_x, error_y, 'DisplayName', 'DRMF', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(cfss_error_comm);
+plot(error_x, error_y, 'DisplayName', 'CFSS', 'LineWidth',line_width);
+
+[error_x, error_y] = cummErrorCurve(tcdcn_error_comm);
+plot(error_x, error_y, 'DisplayName', 'TCDCN', 'LineWidth',line_width);
+
+set(gca,'xtick',[0:0.01:0.1])
+xlim([0.01,0.07]);
+xlabel('IOD normalised MAE','FontName','Helvetica');
+ylabel('Proportion of images','FontName','Helvetica');
+grid on
+% title('Fitting in the wild without outline','FontSize',60,'FontName','Helvetica');
+
+leg = legend('show', 'Location', 'SouthEast');
+set(leg,'FontSize',50)
+
+% Make sure CE-CLM curve is on top
+[error_x, error_y] = cummErrorCurve(ceclm_error_comm);
+plot(error_x, error_y, 'r', 'LineWidth',line_width);
+
+print -dpdf results/ceclm-300W-comm-68.pdf
+print -dpng results/ceclm-300W-comm-68.png

pkg/OpenFace/matlab_version/experiments_300W/Extract_table_results_49.m

@@ -0,0 +1,171 @@
+clear
+
+%% 
+inds_ibug = 562:696;
+
+load('./results/results_clnf_wild.mat');
+labels = experiment.labels([1:60,62:64,66:end],:,:);
+shapes = experiment.shapes([1:60,62:64,66:end],:,:);
+labels = labels(18:end,:,:);
+shapes = shapes(18:end,:,:);
+
+clnf_error_ibug = compute_error( labels(:,:,inds_ibug),  shapes(:,:,inds_ibug) + 1.0);
+
+load('./results/results_ceclm_menpo.mat');
+
+labels = experiment.labels([1:60,62:64,66:end],:,:);
+shapes = experiment.shapes([1:60,62:64,66:end],:,:);
+labels = labels(18:end,:,:);
+shapes = shapes(18:end,:,:);
+
+ceclm_error_ibug = compute_error( labels(:,:,inds_ibug),  shapes(:,:,inds_ibug) + 1.0);
+
+load('results/zhu_wild.mat');
+labels_all = labels_all(18:end,:,:);
+shapes_all = shapes_all(18:end,:,:);
+
+tsm_error_ibug = compute_error(labels_all(:,:,inds_ibug), shapes_all(:,:,inds_ibug));
+
+load('results/CFAN_300W.mat');
+shapes_all = shapes_all([1:60,62:64,66:end],:,:);
+shapes_all = shapes_all(18:end,:,:);
+labels_all = labels_all([1:60,62:64,66:end],:,:);
+labels_all = labels_all(18:end,:,:);
+
+cfan_error_ibug = compute_error(labels_all(:,:,inds_ibug), shapes_all(:,:,inds_ibug)+1.0);
+
+load('./results/results_clm.mat');
+labels = experiment.labels([1:60,62:64,66:end],:,:);
+shapes = experiment.shapes([1:60,62:64,66:end],:,:);
+labels = labels(18:end,:,:);
+shapes = shapes(18:end,:,:);
+clm_error_ibug = compute_error( labels(:,:,inds_ibug),  shapes(:,:,inds_ibug) + 1.0);
+
+load('results/300W_3DDFA.mat');
+shapes = shapes([1:60,62:64,66:end],:,:);
+shapes = shapes(18:end,:,:);
+error_3ddfa_ibug = compute_error( labels_all(:,:,inds_ibug),  shapes(:,:,inds_ibug) + 1.0);
+
+load('results/drmf_wild.mat');
+labels_all = labels_all(18:end,:,:);
+shapes_all = shapes_all(18:end,:,:);
+
+drmf_error_ibug = compute_error(labels_all(:,:,inds_ibug), shapes_all(:,:,inds_ibug));
+
+load('results/300W_sdm.mat');
+shapes_all = experiments.shapes;
+
+sdm_error_ibug = compute_error(labels_all(:,:,inds_ibug), shapes_all(:,:,inds_ibug)+1.5);
+
+load('results/300W_pocr.mat');
+shapes_all = experiments.shapes;
+
+po_cr_error_ibug = compute_error(labels_all(:,:,inds_ibug), shapes_all(:,:,inds_ibug) + 1.0);
+
+load('results/300W-CFSS.mat');
+
+shapes = zeros(size(estimatedPose,2)/2,2,size(estimatedPose,1));
+for i=1:size(estimatedPose,1)
+    xs = estimatedPose(i,1:end/2);
+    ys = estimatedPose(i,end/2+1:end);
+    shapes(:,1,i) = xs;
+    shapes(:,2,i) = ys;
+end
+shapes = shapes([1:60,62:64,66:end],:,:);
+shapes = shapes(18:end,:,:);
+
+cfss_error_ibug = compute_error(labels_all(:,:,inds_ibug), shapes(:,:,inds_ibug)+0.5);
+
+load('results/tcdcn_300W.mat');
+shapes_c = shapes;
+shapes = zeros(68,2,numel(shapes));
+for i=1:numel(shapes_c)
+    xs = shapes_c{i}(:,1);
+    ys = shapes_c{i}(:,2);
+    shapes(:,1,i) = xs;
+    shapes(:,2,i) = ys;
+end
+shapes = shapes([1:60,62:64,66:end],:,:);
+shapes = shapes(18:end,:,:);
+
+tcdcn_error_ibug = compute_error(labels_all(:,:,inds_ibug), shapes(:,:,inds_ibug)+0.5);
+
+%% 
+inds_comm = [338:561,697:1026];
+
+load('./results/results_clnf_wild.mat');
+labels = experiment.labels([1:60,62:64,66:end],:,:);
+shapes = experiment.shapes([1:60,62:64,66:end],:,:);
+labels = labels(18:end,:,:);
+shapes = shapes(18:end,:,:);
+
+clnf_error_comm = compute_error( labels(:,:,inds_comm),  shapes(:,:,inds_comm) + 1.0);
+
+load('./results/results_ceclm_menpo.mat');
+labels = experiment.labels([1:60,62:64,66:end],:,:);
+shapes = experiment.shapes([1:60,62:64,66:end],:,:);
+labels = labels(18:end,:,:);
+shapes = shapes(18:end,:,:);
+
+ceclm_error_comm = compute_error( labels(:,:,inds_comm),  shapes(:,:,inds_comm) + 1.0);
+
+load('results/zhu_wild.mat');
+labels_all = labels_all(18:end,:,:);
+shapes_all = shapes_all(18:end,:,:);
+
+tsm_error_comm = compute_error(labels_all(:,:,inds_comm), shapes_all(:,:,inds_comm));
+
+load('./results/results_clm.mat');
+labels = experiment.labels([1:60,62:64,66:end],:,:);
+shapes = experiment.shapes([1:60,62:64,66:end],:,:);
+labels = labels(18:end,:,:);
+shapes = shapes(18:end,:,:);
+clm_error_comm = compute_error( labels(:,:,inds_comm),  shapes(:,:,inds_comm) + 1.0);
+
+load('results/300W_3DDFA.mat');
+shapes = shapes([1:60,62:64,66:end],:,:);
+shapes = shapes(18:end,:,:);
+error_3ddfa_comm = compute_error( labels_all(:,:,inds_comm),  shapes(:,:,inds_comm)+1.0);
+
+load('results/drmf_wild.mat');
+labels_all = labels_all(18:end,:,:);
+shapes_all = shapes_all(18:end,:,:);
+
+drmf_error_comm = compute_error(labels_all(:,:,inds_comm), shapes_all(:,:,inds_comm));
+
+load('results/300W_sdm.mat');
+shapes_all = experiments.shapes;
+
+sdm_error_comm = compute_error(labels_all(:,:,inds_comm), shapes_all(:,:,inds_comm)+1.5);
+
+load('results/300W_pocr.mat');
+shapes_all = experiments.shapes;
+
+po_cr_error_comm = compute_error(labels_all(:,:,inds_comm), shapes_all(:,:,inds_comm) + 1.0);
+
+load('results/300W-CFSS.mat');
+
+shapes = zeros(size(estimatedPose,2)/2,2,size(estimatedPose,1));
+for i=1:size(estimatedPose,1)
+    xs = estimatedPose(i,1:end/2);
+    ys = estimatedPose(i,end/2+1:end);
+    shapes(:,1,i) = xs;
+    shapes(:,2,i) = ys;
+end
+shapes = shapes([1:60,62:64,66:end],:,:);
+shapes = shapes(18:end,:,:);
+
+cfss_error_comm = compute_error(labels_all(:,:,inds_comm), shapes(:,:,inds_comm)+0.5);
+
+load('results/tcdcn_300W.mat');
+shapes_c = shapes;
+shapes = zeros(68,2,numel(shapes));
+for i=1:numel(shapes_c)
+    xs = shapes_c{i}(:,1);
+    ys = shapes_c{i}(:,2);
+    shapes(:,1,i) = xs;
+    shapes(:,2,i) = ys;
+end
+shapes = shapes([1:60,62:64,66:end],:,:);
+shapes = shapes(18:end,:,:);
+tcdcn_error_comm = compute_error(labels_all(:,:,inds_comm), shapes(:,:,inds_comm)+0.5);

pkg/OpenFace/matlab_version/experiments_300W/Extract_table_results_68.m

@@ -0,0 +1,100 @@
+clear
+
+%% 
+inds_ibug = 562:696;
+
+load('./results/results_clnf_wild.mat');
+
+clnf_error_ibug = compute_error( experiment.labels(:,:,inds_ibug),  experiment.shapes(:,:,inds_ibug) + 1.0);
+
+load('./results/results_ceclm_menpo.mat');
+
+ceclm_error_ibug = compute_error( experiment.labels(:,:,inds_ibug),  experiment.shapes(:,:,inds_ibug) + 1.0);
+
+load('results/zhu_wild.mat');
+
+tsm_error_ibug = compute_error(labels_all(:,:,inds_ibug), shapes_all(:,:,inds_ibug));
+
+load('results/300W_3DDFA.mat');
+error_3ddfa_ibug = compute_error( labels_all(:,:,inds_ibug),  shapes(:,:,inds_ibug) + 1.0);
+
+load('results/results_clm.mat');
+clm_error_ibug = compute_error( experiment.labels(:,:,inds_ibug),  experiment.shapes(:,:,inds_ibug) + 1.0);
+
+load('results/drmf_wild.mat');
+
+drmf_error_ibug = compute_error(labels_all(:,:,inds_ibug), shapes_all(:,:,inds_ibug));
+
+load('results/CFAN_300W.mat');
+
+cfan_error_ibug = compute_error(labels_all(:,:,inds_ibug), shapes_all(:,:,inds_ibug)+1.0);
+
+load('results/300W-CFSS.mat');
+
+shapes = zeros(size(estimatedPose,2)/2,2,size(estimatedPose,1));
+for i=1:size(estimatedPose,1)
+    xs = estimatedPose(i,1:end/2);
+    ys = estimatedPose(i,end/2+1:end);
+    shapes(:,1,i) = xs;
+    shapes(:,2,i) = ys;
+end
+load('results/results_clnf_wild.mat');
+cfss_error_ibug = compute_error(experiment.labels(:,:,inds_ibug), shapes(:,:,inds_ibug)+0.5);
+
+
+load('results/tcdcn_300W.mat');
+shapes_c = shapes;
+shapes = zeros(68,2,numel(shapes));
+for i=1:numel(shapes_c)
+    xs = shapes_c{i}(:,1);
+    ys = shapes_c{i}(:,2);
+    shapes(:,1,i) = xs;
+    shapes(:,2,i) = ys;
+end
+load('results/results_clnf_wild.mat');
+tcdcn_error_ibug = compute_error(experiment.labels(:,:,inds_ibug), shapes(:,:,inds_ibug)+0.5);
+
+%% 
+inds_comm = [338:561,697:1026];
+
+load('./results/results_clnf_wild.mat');
+clnf_error_comm = compute_error( experiment.labels(:,:,inds_comm),  experiment.shapes(:,:,inds_comm) + 1.0);
+
+load('./results/results_ceclm_menpo.mat');
+ceclm_error_comm = compute_error( experiment.labels(:,:,inds_comm),  experiment.shapes(:,:,inds_comm) + 1.0);
+
+load('results/zhu_wild.mat');
+tsm_error_comm = compute_error(labels_all(:,:,inds_comm), shapes_all(:,:,inds_comm));
+
+load('results/results_clm.mat');
+clm_error_comm = compute_error( experiment.labels(:,:,inds_comm),  experiment.shapes(:,:,inds_comm) + 1.0);
+
+load('results/drmf_wild.mat');
+drmf_error_comm = compute_error(labels_all(:,:,inds_comm), shapes_all(:,:,inds_comm));
+
+load('results/300W_3DDFA.mat');
+error_3ddfa_comm = compute_error( labels_all(:,:,inds_comm),  shapes(:,:,inds_comm) + 1.0);
+
+load('results/300W-CFSS.mat');
+shapes = zeros(size(estimatedPose,2)/2,2,size(estimatedPose,1));
+for i=1:size(estimatedPose,1)
+    xs = estimatedPose(i,1:end/2);
+    ys = estimatedPose(i,end/2+1:end);
+    shapes(:,1,i) = xs;
+    shapes(:,2,i) = ys;
+end
+
+load('./results/results_clnf_wild.mat');
+cfss_error_comm = compute_error(experiment.labels(:,:,inds_comm), shapes(:,:,inds_comm)+0.5);
+
+load('results/tcdcn_300W.mat');
+shapes_c = shapes;
+shapes = zeros(68,2,numel(shapes));
+for i=1:numel(shapes_c)
+    xs = shapes_c{i}(:,1);
+    ys = shapes_c{i}(:,2);
+    shapes(:,1,i) = xs;
+    shapes(:,2,i) = ys;
+end
+load('./results/results_clnf_wild.mat');
+tcdcn_error_comm = compute_error(experiment.labels(:,:,inds_comm), shapes(:,:,inds_comm)+0.5);

pkg/OpenFace/matlab_version/experiments_300W/Script_CECLM_general.m

@@ -0,0 +1,99 @@
+function Script_CECLM_general()
+
+addpath(genpath('../'));
+
+% Replace this with the location of the 300W data location
+if(exist([getenv('USERPROFILE') '/Dropbox/AAM/test data/'], 'file'))
+    root_test_data = [getenv('USERPROFILE') '/Dropbox/AAM/test data/'];    
+else
+    root_test_data = 'F:\Dropbox\AAM\test data/';
+end
+[images, detections, labels] = Collect_wild_imgs(root_test_data);
+
+%% loading the CE-CLM model and parameters   
+[patches, pdm, clmParams, early_term_params] = Load_CECLM_general();
+% Use the multi-hypothesis model, as bounding box tells nothing about
+% orientation
+views = [0,0,0; 0,-30,0; 0,30,0; 0,0,30; 0,0,-30;];
+views = views * pi/180;                                                                                     
+
+%% Setup recording
+
+num_points = numel(pdm.M)/3;
+
+shapes_all = zeros(size(labels,2),size(labels,3), size(labels,1));
+labels_all = zeros(size(labels,2),size(labels,3), size(labels,1));
+lhoods = zeros(numel(images),1);
+all_lmark_lhoods = zeros(num_points, numel(images));
+all_views_used = zeros(numel(images),1);
+
+% Change if you want to visualize the outputs
+verbose = false;
+output_img = false;
+
+if(output_img)
+    output_root = './ceclm_gen_out/';
+    if(~exist(output_root, 'dir'))
+        mkdir(output_root);
+    end
+end
+if(verbose)
+    f = figure;
+end
+
+%% Fitting the model to the provided images
+
+tic
+for i=1:numel(images)
+
+    image = imread(images(i).img);
+    image_orig = image;
+    
+    if(size(image,3) == 3)
+        image = rgb2gray(image);
+    end              
+
+    bbox = detections(i,:);                  
+    
+    [shape,~,~,lhood,lmark_lhood,view_used] =...
+        Fitting_from_bb_multi_hyp(image, [], bbox, pdm, patches, clmParams, views, early_term_params);
+
+    all_lmark_lhoods(:,i) = lmark_lhood;
+    all_views_used(i) = view_used;
+
+    shapes_all(:,:,i) = shape;
+    labels_all(:,:,i) = labels(i,:,:);
+
+    if(mod(i, 200)==0)
+        fprintf('%d done\n', i );
+    end
+
+    lhoods(i) = lhood;
+
+    if(output_img)
+        v_points = sum(squeeze(labels(i,:,:)),2) > 0;
+        DrawFaceOnImg(image_orig, shape, sprintf('%s/%s%d.jpg', output_root, 'fit', i), bbox, v_points);
+    end
+    
+    if(verbose)
+        v_points = sum(squeeze(labels(i,:,:)),2) > 0;
+        DrawFaceOnFig(image_orig, shape, bbox, v_points);
+    end
+end
+toc
+
+experiment.errors_normed = compute_error(labels_all, shapes_all + 1.0);
+experiment.lhoods = lhoods;
+experiment.shapes = shapes_all;
+experiment.labels = labels_all;
+experiment.all_lmark_lhoods = all_lmark_lhoods;
+experiment.all_views_used = all_views_used;
+
+fprintf('Done: mean normed error %.3f median normed error %.4f\n', ...
+    mean(experiment.errors_normed), median(experiment.errors_normed));
+
+%%
+output_results = 'results/results_ceclm_general.mat';
+save(output_results, 'experiment');
+    
+end

pkg/OpenFace/matlab_version/experiments_300W/Script_CECLM_menpo.m

@@ -0,0 +1,101 @@
+function Script_CECLM_menpo()
+
+addpath(genpath('../'));
+
+% Replace this with the location of the 300W data location
+if(exist([getenv('USERPROFILE') '/Dropbox/AAM/test data/'], 'file'))
+    root_test_data = [getenv('USERPROFILE') '/Dropbox/AAM/test data/'];    
+else
+    root_test_data = 'F:\Dropbox\AAM\test data/';
+end
+[images, detections, labels] = Collect_wild_imgs(root_test_data);
+
+%% loading the CE-CLM model and parameters   
+[patches, pdm, clmParams, early_term_params] = Load_CECLM_menpo();
+% Use the multi-hypothesis model, as bounding box tells nothing about
+% orientation
+views = [0,0,0; 0,-30,0; 0,30,0; 0,0,30; 0,0,-30;];
+views = views * pi/180;                                                                                     
+
+%% Setup recording
+
+num_points = numel(pdm.M)/3;
+
+shapes_all = zeros(size(labels,2),size(labels,3), size(labels,1));
+labels_all = zeros(size(labels,2),size(labels,3), size(labels,1));
+lhoods = zeros(numel(images),1);
+all_lmark_lhoods = zeros(num_points, numel(images));
+all_views_used = zeros(numel(images),1);
+
+% Change if you want to visualize the outputs
+verbose = true;
+output_img = false;
+
+if(output_img)
+    output_root = './ceclm_menpo_out/';
+    if(~exist(output_root, 'dir'))
+        mkdir(output_root);
+    end
+end
+if(verbose)
+    f = figure;
+end
+
+
+%% Fitting the model to the provided images
+
+tic
+for i=1:numel(images)
+
+    image = imread(images(i).img);
+    image_orig = image;
+    
+    if(size(image,3) == 3)
+        image = rgb2gray(image);
+    end              
+
+    bbox = detections(i,:);                  
+    
+    % have a multi-view version
+    [shape,~,~,lhood,lmark_lhood,view_used] =...
+        Fitting_from_bb_multi_hyp(image, [], bbox, pdm, patches, clmParams, views, early_term_params);
+
+    all_lmark_lhoods(:,i) = lmark_lhood;
+    all_views_used(i) = view_used;
+
+    shapes_all(:,:,i) = shape;
+    labels_all(:,:,i) = labels(i,:,:);
+
+    if(mod(i, 200)==0)
+        fprintf('%d done\n', i );
+    end
+
+    lhoods(i) = lhood;
+
+    if(output_img)
+        v_points = sum(squeeze(labels(i,:,:)),2) > 0;
+        DrawFaceOnImg(image_orig, shape, sprintf('%s/%s%d.jpg', output_root, 'fit', i), bbox, v_points);
+    end
+    
+    if(verbose)
+        v_points = sum(squeeze(labels(i,:,:)),2) > 0;
+        DrawFaceOnFig(image_orig, shape, bbox, v_points);
+    end
+end
+toc
+
+experiment.errors_normed = compute_error(labels_all, shapes_all + 1.0);
+experiment.lhoods = lhoods;
+experiment.shapes = shapes_all;
+experiment.labels = labels_all;
+experiment.all_lmark_lhoods = all_lmark_lhoods;
+experiment.all_views_used = all_views_used;
+
+fprintf('Done: mean normed error %.3f median normed error %.4f\n', ...
+    mean(experiment.errors_normed), median(experiment.errors_normed));
+
+%%
+output_results = 'results/results_ceclm_menpo.mat';
+save(output_results, 'experiment');
+    
+end

pkg/OpenFace/matlab_version/experiments_300W/Script_CLM.m

@@ -0,0 +1,104 @@
+function Script_CLM()
+
+addpath(genpath('../'));
+
+% Replace this with the location of in 300 faces in the wild data
+if(exist([getenv('USERPROFILE') '/Dropbox/AAM/test data/'], 'file'))
+    root_test_data = [getenv('USERPROFILE') '/Dropbox/AAM/test data/'];    
+else
+    root_test_data = 'F:\Dropbox\AAM\test data/';
+end
+
+[images, detections, labels] = Collect_wild_imgs(root_test_data);
+
+%% loading the patch experts
+   
+[ patches, pdm, clmParams ] = Load_CLM_wild();
+
+% Defining the view orientations that will be evaluated
+%views = [0,0,0];
+views = [0,0,0; 0,-30,0; 0,30,0; 0,0,30; 0,0,-30;];
+views = views * pi/180;                                                                                     
+
+%% Fitting the model to the provided image
+
+% Change if you want to visualize the outputs
+verbose = true;
+output_img = false;
+
+if(output_img)
+    output_root = './clm_out/';
+    if(~exist(output_root, 'dir'))
+        mkdir(output_root);
+    end
+end
+if(verbose)
+    f = figure;
+end
+   
+% for recording purposes
+
+num_points = numel(pdm.M)/3;
+
+shapes_all = zeros(size(labels,2),size(labels,3), size(labels,1));
+labels_all = zeros(size(labels,2),size(labels,3), size(labels,1));
+lhoods = zeros(numel(images),1);
+all_lmark_lhoods = zeros(num_points, numel(images));
+all_views_used = zeros(numel(images),1);
+
+% Use the multi-hypothesis model, as bounding box tells nothing about
+% orientation
+multi_view = false;
+
+tic
+for i=1:numel(images)
+
+    image = imread(images(i).img);
+    image_orig = image;
+
+    if(size(image,3) == 3)
+        image = rgb2gray(image);
+    end              
+
+    bbox = detections(i,:);
+    
+    [shape,~,~,lhood,lmark_lhood,view_used] = Fitting_from_bb_multi_hyp(image, [], bbox, pdm, patches, clmParams, views);
+        
+    all_lmark_lhoods(:,i) = lmark_lhood;
+    all_views_used(i) = view_used;
+
+    shapes_all(:,:,i) = shape;
+    labels_all(:,:,i) = labels(i,:,:);
+
+    if(mod(i, 100)==0)
+        fprintf('%d done\n', i );
+    end
+        
+    lhoods(i) = lhood;
+    
+    if(output_img)
+        v_points = sum(squeeze(labels(i,:,:)),2) > 0;
+        DrawFaceOnImg(image_orig, shape, sprintf('%s/%s%d.jpg', output_root, 'fit', i), bbox, v_points);
+    end
+    
+    if(verbose)
+        v_points = sum(squeeze(labels(i,:,:)),2) > 0;
+        DrawFaceOnFig(image_orig, shape, bbox, v_points);
+    end
+
+end
+toc
+experiment.errors_normed = compute_error(labels_all, shapes_all + 1.0);
+experiment.lhoods = lhoods;
+experiment.shapes = shapes_all;
+experiment.labels = labels_all;
+experiment.all_lmark_lhoods = all_lmark_lhoods;
+experiment.all_views_used = all_views_used;
+
+fprintf('Done: mean normed error %.3f median normed error %.4f\n', ...
+    mean(experiment.errors_normed), median(experiment.errors_normed));
+%%
+output_results = 'results/results_clm.mat';
+save(output_results, 'experiment');
+    
+end

pkg/OpenFace/matlab_version/experiments_300W/Script_CLNF_general.m

@@ -0,0 +1,96 @@
+function Script_CLNF_general()
+
+addpath(genpath('../'));
+
+% Replace this with the location of in 300 faces in the wild data
+if(exist([getenv('USERPROFILE') '/Dropbox/AAM/test data/'], 'file'))
+    root_test_data = [getenv('USERPROFILE') '/Dropbox/AAM/test data/'];    
+else
+    root_test_data = 'F:\Dropbox\AAM\test data/';
+end
+
+[images, detections, labels] = Collect_wild_imgs(root_test_data);
+%% loading the patch experts and pdms
+
+[ patches, pdm, clmParams ] = Load_CLNF_general();
+views = [0,0,0; 0,-30,0; 0,30,0; 0,0,30; 0,0,-30;];
+views = views * pi/180;                                                                                     
+
+[ patches_51, pdm_51, clmParams_51, inds_full, inds_inner ] = Load_CLNF_inner();
+
+%% Change if you want to visualize the outputs
+verbose = false;
+output_img = false;
+
+if(output_img)
+    output_root = './clnf_out_general/';
+    if(~exist(output_root, 'dir'))
+        mkdir(output_root);
+    end
+end
+if(verbose)
+    f = figure;
+end
+
+%% For recording
+
+shapes_all = zeros(size(labels,2),size(labels,3), size(labels,1));
+labels_all = zeros(size(labels,2),size(labels,3), size(labels,1));
+lhoods = zeros(numel(images),1);
+
+
+%% Fitting the model to the provided image
+
+tic
+for i=1:numel(images)
+
+    image = imread(images(i).img);
+    image_orig = image;
+
+    if(size(image,3) == 3)
+        image = rgb2gray(image);
+    end              
+
+    bbox = detections(i,:);                  
+
+    [shape,~,~,lhood,lmark_lhood,view_used] = Fitting_from_bb_multi_hyp(image, [], bbox, pdm, patches, clmParams, views);
+             
+    % Perform inner landmark fitting now
+    [shape, shape_inner] = Fitting_from_bb_hierarch(image, pdm, pdm_51, patches_51, clmParams_51, shape, inds_full, inds_inner);
+
+    shapes_all(:,:,i) = shape;
+
+    labels_all(:,:,i) = labels(i,:,:);
+
+    if(mod(i, 200)==0)
+        fprintf('%d done\n', i );
+    end
+
+    lhoods(i) = lhood;
+
+    if(output_img)
+        v_points = sum(squeeze(labels(i,:,:)),2) > 0;
+        DrawFaceOnImg(image_orig, shape, sprintf('%s/%s%d.jpg', output_root, 'fit', i), bbox, v_points);
+    end
+    
+    if(verbose)
+        v_points = sum(squeeze(labels(i,:,:)),2) > 0;
+        DrawFaceOnFig(image_orig, shape, bbox, v_points);
+    end
+
+end
+toc
+
+experiment.errors_normed = compute_error(labels_all, shapes_all + 1.0);
+experiment.lhoods = lhoods;
+experiment.shapes = shapes_all;
+experiment.labels = labels_all;
+
+fprintf('Done: mean normed error %.3f median normed error %.4f\n', ...
+    mean(experiment.errors_normed), median(experiment.errors_normed));
+
+%%
+output_results = 'results/results_clnf_general.mat';
+save(output_results, 'experiment');
+    
+end

pkg/OpenFace/matlab_version/experiments_300W/Script_CLNF_wild.m

@@ -0,0 +1,97 @@
+function Script_CLNF_wild()
+
+addpath(genpath('../'));
+
+% Replace this with the location of in 300 faces in the wild data
+if(exist([getenv('USERPROFILE') '/Dropbox/AAM/test data/'], 'file'))
+    root_test_data = [getenv('USERPROFILE') '/Dropbox/AAM/test data/'];    
+else
+    root_test_data = 'F:\Dropbox\AAM\test data/';
+end
+
+[images, detections, labels] = Collect_wild_imgs(root_test_data);
+%% loading the patch experts and pdms
+   
+[ patches, pdm, clmParams ] = Load_CLNF_wild();
+%views = [0,0,0];
+% Use the multi-hypothesis model, as bounding box tells nothing about
+% orientation
+views = [0,0,0; 0,-30,0; 0,30,0; 0,0,30; 0,0,-30;];
+views = views * pi/180;                                                                                     
+
+% for recording purposes
+experiment.params = clmParams;
+
+%% Change if you want to visualize the outputs
+verbose = false;
+output_img = false;
+
+if(output_img)
+    output_root = './clnf_out_wild/';
+    if(~exist(output_root, 'dir'))
+        mkdir(output_root);
+    end
+end
+if(verbose)
+    f = figure;
+end
+
+%% For recording
+
+shapes_all = zeros(size(labels,2),size(labels,3), size(labels,1));
+labels_all = zeros(size(labels,2),size(labels,3), size(labels,1));
+lhoods = zeros(numel(images),1);
+
+%% Fitting the model to the provided image
+
+tic
+for i=1:numel(images)
+
+    image = imread(images(i).img);
+    image_orig = image;
+
+    if(size(image,3) == 3)
+        image = rgb2gray(image);
+    end              
+
+    bbox = detections(i,:);                  
+
+    [shape,~,~,lhood,lmark_lhood,view_used] = Fitting_from_bb_multi_hyp(image, [], bbox, pdm, patches, clmParams, views);
+
+    shapes_all(:,:,i) = shape;                    
+
+    labels_all(:,:,i) = labels(i,:,:);
+
+    if(mod(i, 200)==0)
+        fprintf('%d done\n', i );
+    end
+
+    lhoods(i) = lhood;
+
+    
+    if(output_img)
+        v_points = sum(squeeze(labels(i,:,:)),2) > 0;
+        DrawFaceOnImg(image_orig, shape, sprintf('%s/%s%d.jpg', output_root, 'fit', i), bbox, v_points);
+    end
+    
+    if(verbose)
+        v_points = sum(squeeze(labels(i,:,:)),2) > 0;
+        DrawFaceOnFig(image_orig, shape, bbox, v_points);
+    end
+
+end
+toc
+
+experiment.errors_normed = compute_error(labels_all, shapes_all + 1.0);
+experiment.lhoods = lhoods;
+experiment.shapes = shapes_all;
+experiment.labels = labels_all;
+
+fprintf('Done: mean normed error %.3f median normed error %.4f\n', ...
+    mean(experiment.errors_normed), median(experiment.errors_normed));
+
+%%
+output_results = 'results/results_clnf_wild.mat';
+save(output_results, 'experiment');
+    
+end

pkg/OpenFace/matlab_version/experiments_300W/comp_error_pts.m

@@ -0,0 +1,45 @@
+%gts
+
+dirs = {'../../test data/AFW/';
+    '../../test data/ibug/';
+    '../../test data/helen/testset/';
+    '../../test data/lfpw/testset/';};
+
+landmark_dets = dir('out_clnf_cpp\*.pts');
+
+landmark_det_dir = 'out_clnf_cpp\';
+
+num_imgs = size(landmark_dets,1);
+
+labels = zeros(68,2,num_imgs);
+shapes = zeros(68,2,num_imgs);
+
+landmark_gt = dir(['../../test data/AFW/*.pts']);
+
+curr = 0;
+
+for i=1:numel(dirs)
+    
+    curr = curr+1;
+    
+    gt_labels = dir([dirs{i}, '*.pts']);
+    
+    for g=1:numel(gt_labels)
+           gt_landmarks = importdata([dirs{i}, gt_labels(g).name], ' ', 3);
+           gt_landmarks = gt_landmarks.data;
+ 
+           % find the corresponding detection
+           
+           landmark_det = importdata([landmark_det_dir, gt_labels(g).name], ' ', 3);
+           landmark_det = landmark_det.data;
+           
+           labels(:,:,curr) = gt_landmarks;
+           shapes(:,:,curr) = landmark_det;
+           
+    end
+    
+end
+
+
+
+

pkg/OpenFace/matlab_version/experiments_300W/compute_error.m

@@ -0,0 +1,34 @@
+function [ error_per_image ] = compute_error( ground_truth_all, detected_points_all )
+%compute_error
+%   compute the average point-to-point Euclidean error normalized by the
+%   inter-ocular distance (measured as the Euclidean distance between the
+%   outer corners of the eyes)
+%
+%   Inputs:
+%          grounth_truth_all, size: num_of_points x 2 x num_of_images
+%          detected_points_all, size: num_of_points x 2 x num_of_images
+%   Output:
+%          error_per_image, size: num_of_images x 1
+
+
+num_of_images = size(ground_truth_all,3);
+num_of_points = size(ground_truth_all,1);
+
+error_per_image = zeros(num_of_images,1);
+
+for i =1:num_of_images
+    detected_points      = detected_points_all(:,:,i);
+    ground_truth_points  = ground_truth_all(:,:,i);
+    if(num_of_points == 66 || num_of_points == 68)
+        interocular_distance = norm(ground_truth_points(37,:)-ground_truth_points(46,:));
+    else
+        interocular_distance = norm(ground_truth_points(37-17,:)-ground_truth_points(46-17,:));
+    end
+    sum=0;
+    for j=1:num_of_points
+        sum = sum+norm(detected_points(j,:)-ground_truth_points(j,:));
+    end
+    error_per_image(i) = sum/(num_of_points*interocular_distance);
+end
+
+end

pkg/OpenFace/matlab_version/experiments_300W/cummErrorCurve.m

@@ -0,0 +1,19 @@
+function [x, y] = cummErrorCurve( errorVec )
+%CUMMERRORCURVE Summary of this function goes here
+%   Detailed explanation goes here
+
+    
+    spacing = 0.001;       
+    
+    sampling = [0:spacing:max(errorVec)];
+
+    x = sampling;
+    
+    y = zeros(numel(sampling,1));
+    
+    for i=1:numel(sampling)
+    
+        y(i) = sum(errorVec < sampling(i)) / numel(errorVec);
+    end
+end
+

pkg/OpenFace/matlab_version/experiments_300W/readme.txt

@@ -0,0 +1,18 @@
+Scripts for evaluating CE-CLM, CLNF, and CLM methods on the 300W challenge dataset - https://ibug.doc.ic.ac.uk/resources/300-W/
+
+To run the models on the data using models trained on 300W + MultiPIE:
+- Script_CECLM_general.m
+- Script_CLNF_general.m
+- Script_CLM.m
+
+To run CE-CLM model trained on 300W + MultiPIE + Menpo:
+- Script CECLM_menpo.m
+
+To visualize the results of the models against baselines (using inner face markup - 49, and full face markup - 68):
+Display_ceclm_results_49.m
+Display_ceclm_results_68.m
+
+To construct the error table:
+Construct_error_table.m
+
+For a fair comparison all the models and baselines are initialized using the bounding boxes provided by the challenge authors.

pkg/OpenFace/matlab_version/experiments_300W/results/300W_49.txt

@@ -0,0 +1,12 @@
+Errors without outline (49 points)
+------------------------------
+Method	comm	diff
+CLNF	2.51	4.93
+SDM 	3.31	10.73
+CFAN	--- 	6.99
+DRMF	4.22	8.64
+CFSS	2.46	4.49
+TCDCN	3.32	5.56
+3DDFA	5.17	8.34
+------------------------------
+CE-CLM	2.31	3.91

pkg/OpenFace/matlab_version/experiments_300W/results/300W_68.txt

@@ -0,0 +1,11 @@
+Errors with outline (68 points)
+------------------------------
+Method	comm	diff
+CLNF	3.47	6.37
+CFAN	--- 	8.38
+DRMF	4.97	10.36
+CFSS	3.20	5.97
+TCDCN	4.11	6.87
+3DDFA	7.27	12.31
+------------------------------
+CE-CLM	3.16	5.35