open source pkg v1

pkg/OpenFace/matlab_runners/Demos/Read_HOG_file.m

@@ -0,0 +1,59 @@
+function [hog_data, valid_inds] = Read_HOG_file(hog_file)
+
+    valid_inds = [];
+            
+    f = fopen(hog_file, 'r');
+
+    % Pre-allocated data
+    curr_data = [];
+    curr_ind = 0;
+
+    while(~feof(f))
+
+        if(curr_ind == 0)
+            num_cols = fread(f, 1, 'int32');
+            if(isempty(num_cols))
+                break;
+            end
+
+            num_rows = fread(f, 1, 'int32');
+            num_chan = fread(f, 1, 'int32');
+
+            curr_ind = curr_ind + 1;            
+
+            % preallocate some space
+            if(curr_ind == 1)
+                curr_data = zeros(1000, 1 + num_rows * num_cols * num_chan);
+                num_feats =  1 + num_rows * num_cols * num_chan;
+            end
+
+            if(curr_ind > size(curr_data,1))
+                curr_data = cat(1, curr_data, zeros(1000, 1 + num_rows * num_cols * num_chan));
+            end
+            feature_vec = fread(f, [1, 1 + num_rows * num_cols * num_chan], 'float32');
+            curr_data(curr_ind, :) = feature_vec;
+        else
+
+            % Reading in batches of 5000
+
+            feature_vec = fread(f, [4 + num_rows * num_cols * num_chan, 5000], 'float32');
+            feature_vec = feature_vec(4:end,:)';
+
+            num_rows_read = size(feature_vec,1);
+
+            if(~isempty(feature_vec))
+                curr_data(curr_ind+1:curr_ind+num_rows_read,:) = feature_vec;
+                curr_ind = curr_ind + size(feature_vec,1);
+            end
+        end
+
+    end
+
+    fclose(f);
+
+    % Do some cleanup, remove un-allocated data    
+    if(~isempty(curr_data))        
+        valid_inds = curr_data(1:curr_ind,1);
+        hog_data = curr_data(1:curr_ind,2:end);    
+    end
+end

pkg/OpenFace/matlab_runners/Demos/feature_extraction_demo_img_seq.m

@@ -0,0 +1,179 @@
+% A demo script that demonstrates how to process a single video file using
+% OpenFace and extract and visualize all of the features
+
+clear
+
+% The location executable will depend on the OS
+if(isunix)
+    executable = '"../../build/bin/FeatureExtraction"';
+else
+    executable = '"../../x64/Release/FeatureExtraction.exe"';
+end
+
+% Input file
+in_dir = '../../samples/image_sequence';
+
+% Where to store the output
+output_dir = './processed_features/';
+
+% This will take directory after -fdir and output all the features to directory
+% after -out_dir
+command = sprintf('%s -fdir "%s" -out_dir "%s" -verbose', executable, in_dir, output_dir);
+                 
+if(isunix)
+    unix(command);
+else
+    dos(command);
+end
+
+%% Demonstrating reading the output files
+
+% Most of the features will be in the csv file in the output directory with
+% the same name as the input file
+[~,name,~] = fileparts(in_dir);
+output_csv = sprintf('%s/%s.csv', output_dir, name);
+
+% First read in the column names, to know which columns to read for
+% particular features
+tab = readtable(output_csv);
+column_names = tab.Properties.VariableNames;
+
+% Read all of the data
+all_params  = dlmread(output_csv, ',', 1, 0);
+
+% This indicates which frames were succesfully tracked
+
+% Find which column contains success of tracking data and timestamp data
+valid_ind = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'success'));
+frame_ind = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'frame'));
+
+% Extract tracking success data and only read those frame
+valid_frames = logical(all_params(:,valid_ind));
+
+% Get the timestamp data
+frame_nums = all_params(valid_frames, frame_ind);
+
+%% Finding which header line starts with p_ (basically model params)
+shape_inds = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'p_'));
+
+% Output rigid (first 6) and non-rigid shape parameters
+shape_params  = all_params(valid_frames, shape_inds);
+
+figure
+plot(frame_nums, shape_params);
+title('Shape parameters');
+xlabel('Frame');
+
+%% Demonstrate 2D landmarks
+landmark_inds_x = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'x_'));
+landmark_inds_y = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'y_'));
+
+xs = all_params(valid_frames, landmark_inds_x);
+ys = all_params(valid_frames, landmark_inds_y);
+
+eye_landmark_inds_x = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'eye_lmk_x_'));
+eye_landmark_inds_y = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'eye_lmk_y_'));
+
+eye_xs = all_params(valid_frames, eye_landmark_inds_x);
+eye_ys = all_params(valid_frames, eye_landmark_inds_y);
+
+figure
+
+for j = 1:size(xs,1)
+    plot(xs(j,:), -ys(j,:), '.');
+    hold on;
+    plot(eye_xs(j,:), -eye_ys(j,:), '.r');
+    hold off;
+    
+    xlim([min(xs(1,:)) * 0.5, max(xs(2,:))*1.4]);
+    ylim([min(-ys(1,:)) * 1.4, max(-ys(2,:))*0.5]);
+    xlabel('x (px)');
+    ylabel('y (px)');
+    drawnow
+end
+
+
+%% Demonstrate 3D landmarks
+landmark_inds_x = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'X_'));
+landmark_inds_y = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'Y_'));
+landmark_inds_z = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'Z_'));
+
+xs = all_params(valid_frames, landmark_inds_x);
+ys = all_params(valid_frames, landmark_inds_y);
+zs = all_params(valid_frames, landmark_inds_z);
+
+eye_landmark_inds_x = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'eye_lmk_X_'));
+eye_landmark_inds_y = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'eye_lmk_Y_'));
+eye_landmark_inds_z = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'eye_lmk_Z_'));
+
+eye_xs = all_params(valid_frames, eye_landmark_inds_x);
+eye_ys = all_params(valid_frames, eye_landmark_inds_y);
+eye_zs = all_params(valid_frames, eye_landmark_inds_z);
+
+figure
+for j = 1:size(xs,1)
+    plot3(xs(j,:), ys(j,:), zs(j,:), '.');axis equal;
+    hold on;
+    plot3(eye_xs(j,:), eye_ys(j,:), eye_zs(j,:), '.r');
+    hold off;
+    xlabel('X (mm)');
+    ylabel('Y (mm)');    
+    zlabel('Z (mm)');    
+    drawnow
+end
+
+%% Demonstrate AUs
+au_reg_inds = cellfun(@(x) ~isempty(x) && x==5, strfind(column_names, '_r'));
+
+aus = all_params(valid_frames, au_reg_inds);
+figure
+plot(frame_nums, aus);
+title('Facial Action Units (intensity)');
+xlabel('Time (s)');
+ylabel('Intensity');
+ylim([0,6]);
+
+au_class_inds = cellfun(@(x) ~isempty(x) && x==5, strfind(column_names, '_c'));
+
+aus = all_params(valid_frames, au_class_inds);
+figure
+plot(frame_nums, aus);
+title('Facial Action Units (presense)');
+xlabel('Time (s)');
+ylim([0,2]);
+%% Demo pose
+pose_inds = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'pose_'));
+
+pose = all_params(valid_frames, pose_inds);
+figure
+plot(frame_nums, pose);
+title('Pose (rotation and translation)');
+xlabel('Frame number');
+
+%% Demo gaze
+gaze_inds = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'gaze_angle'));
+
+% Read gaze (x,y,z) for one eye and (x,y,z) for another
+gaze = all_params(valid_frames, gaze_inds);
+
+plot(frame_nums, gaze(:,1), 'DisplayName', 'Left - right');
+hold on;
+plot(frame_nums, gaze(:,2), 'DisplayName', 'Up - down');
+xlabel('Frame number') % x-axis label
+ylabel('Angle radians') % y-axis label
+legend('show');
+hold off;
+
+%% Output HOG files
+output_hog_file = sprintf('%s/%s.hog', output_dir, name);
+[hog_data, valid_inds] = Read_HOG_file(output_hog_file);
+
+%% Output aligned images
+output_aligned_dir = sprintf('%s/%s_aligned/', output_dir, name);
+img_files = dir([output_aligned_dir, '/*.bmp']);
+imgs = cell(numel(img_files, 1));
+for i=1:numel(img_files)
+   imgs{i} = imread([ output_aligned_dir, '/', img_files(i).name]);
+   imshow(imgs{i})
+   drawnow
+end

pkg/OpenFace/matlab_runners/Demos/feature_extraction_demo_vid.m

@@ -0,0 +1,179 @@
+% A demo script that demonstrates how to process a single video file using
+% OpenFace and extract and visualize all of the features
+
+clear
+
+% The location executable will depend on the OS
+if(isunix)
+    executable = '"../../build/bin/FeatureExtraction"';
+else
+    executable = '"../../x64/Release/FeatureExtraction.exe"';
+end
+
+% Input file
+in_file = '../../samples/default.wmv';
+
+% Where to store the output
+output_dir = './processed_features/';
+
+% This will take file after -f and output all the features to directory
+% after -out_dir
+command = sprintf('%s -f "%s" -out_dir "%s" -verbose', executable, in_file, output_dir);
+                 
+if(isunix)
+    unix(command);
+else
+    dos(command);
+end
+
+%% Demonstrating reading the output files
+
+% Most of the features will be in the csv file in the output directory with
+% the same name as the input file
+[~,name,~] = fileparts(in_file);
+output_csv = sprintf('%s/%s.csv', output_dir, name);
+
+% First read in the column names, to know which columns to read for
+% particular features
+tab = readtable(output_csv);
+column_names = tab.Properties.VariableNames;
+
+% Read all of the data
+all_params  = dlmread(output_csv, ',', 1, 0);
+
+% This indicates which frames were succesfully tracked
+
+% Find which column contains success of tracking data and timestamp data
+valid_ind = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'success'));
+time_stamp_ind = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'timestamp'));
+
+% Extract tracking success data and only read those frame
+valid_frames = logical(all_params(:,valid_ind));
+
+% Get the timestamp data
+time_stamps = all_params(valid_frames, time_stamp_ind);
+
+%% Finding which header line starts with p_ (basically model params)
+shape_inds = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'p_'));
+
+% Output rigid (first 6) and non-rigid shape parameters
+shape_params  = all_params(valid_frames, shape_inds);
+
+figure
+plot(time_stamps, shape_params);
+title('Shape parameters');
+xlabel('Time (s)');
+
+%% Demonstrate 2D landmarks
+landmark_inds_x = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'x_'));
+landmark_inds_y = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'y_'));
+
+xs = all_params(valid_frames, landmark_inds_x);
+ys = all_params(valid_frames, landmark_inds_y);
+
+eye_landmark_inds_x = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'eye_lmk_x_'));
+eye_landmark_inds_y = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'eye_lmk_y_'));
+
+eye_xs = all_params(valid_frames, eye_landmark_inds_x);
+eye_ys = all_params(valid_frames, eye_landmark_inds_y);
+
+figure
+
+for j = 1:size(xs,1)
+    plot(xs(j,:), -ys(j,:), '.');
+    hold on;
+    plot(eye_xs(j,:), -eye_ys(j,:), '.r');
+    hold off;
+    
+    xlim([min(xs(1,:)) * 0.5, max(xs(2,:))*1.4]);
+    ylim([min(-ys(1,:)) * 1.4, max(-ys(2,:))*0.5]);
+    xlabel('x (px)');
+    ylabel('y (px)');
+    drawnow
+end
+
+
+%% Demonstrate 3D landmarks
+landmark_inds_x = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'X_'));
+landmark_inds_y = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'Y_'));
+landmark_inds_z = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'Z_'));
+
+xs = all_params(valid_frames, landmark_inds_x);
+ys = all_params(valid_frames, landmark_inds_y);
+zs = all_params(valid_frames, landmark_inds_z);
+
+eye_landmark_inds_x = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'eye_lmk_X_'));
+eye_landmark_inds_y = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'eye_lmk_Y_'));
+eye_landmark_inds_z = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'eye_lmk_Z_'));
+
+eye_xs = all_params(valid_frames, eye_landmark_inds_x);
+eye_ys = all_params(valid_frames, eye_landmark_inds_y);
+eye_zs = all_params(valid_frames, eye_landmark_inds_z);
+
+figure
+for j = 1:size(xs,1)
+    plot3(xs(j,:), ys(j,:), zs(j,:), '.');axis equal;
+    hold on;
+    plot3(eye_xs(j,:), eye_ys(j,:), eye_zs(j,:), '.r');
+    hold off;
+    xlabel('X (mm)');
+    ylabel('Y (mm)');    
+    zlabel('Z (mm)');    
+    drawnow
+end
+
+%% Demonstrate AUs
+au_reg_inds = cellfun(@(x) ~isempty(x) && x==5, strfind(column_names, '_r'));
+
+aus = all_params(valid_frames, au_reg_inds);
+figure
+plot(time_stamps, aus);
+title('Facial Action Units (intensity)');
+xlabel('Time (s)');
+ylabel('Intensity');
+ylim([0,6]);
+
+au_class_inds = cellfun(@(x) ~isempty(x) && x==5, strfind(column_names, '_c'));
+
+aus = all_params(valid_frames, au_class_inds);
+figure
+plot(time_stamps, aus);
+title('Facial Action Units (presense)');
+xlabel('Time (s)');
+ylim([0,2]);
+%% Demo pose
+pose_inds = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'pose_'));
+
+pose = all_params(valid_frames, pose_inds);
+figure
+plot(time_stamps, pose);
+title('Pose (rotation and translation)');
+xlabel('Time (s)');
+
+%% Demo gaze
+gaze_inds = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'gaze_angle'));
+
+% Read gaze (x,y,z) for one eye and (x,y,z) for another
+gaze = all_params(valid_frames, gaze_inds);
+
+plot(time_stamps, gaze(:,1), 'DisplayName', 'Left - right');
+hold on;
+plot(time_stamps, gaze(:,2), 'DisplayName', 'Up - down');
+xlabel('Time(s)') % x-axis label
+ylabel('Angle radians') % y-axis label
+legend('show');
+hold off;
+
+%% Output HOG files
+output_hog_file = sprintf('%s/%s.hog', output_dir, name);
+[hog_data, valid_inds] = Read_HOG_file(output_hog_file);
+
+%% Output aligned images
+output_aligned_dir = sprintf('%s/%s_aligned/', output_dir, name);
+img_files = dir([output_aligned_dir, '/*.bmp']);
+imgs = cell(numel(img_files, 1));
+for i=1:numel(img_files)
+   imgs{i} = imread([ output_aligned_dir, '/', img_files(i).name]);
+   imshow(imgs{i})
+   drawnow
+end

pkg/OpenFace/matlab_runners/Demos/gaze_extraction_demo_vid.m

@@ -0,0 +1,41 @@
+clear
+
+if(isunix)
+    executable = '"../../build/bin/FeatureExtraction"';
+else
+    executable = '"../../x64/Release/FeatureExtraction.exe"';
+end
+
+output = './processed_features/';
+    
+in_file = '../../samples/2015-10-15-15-14.avi';
+
+command = sprintf('%s -f "%s" -out_dir "%s" -gaze -verbose', executable, in_file, output);
+    
+if(isunix)
+    unix(command);
+else
+    dos(command);
+end
+
+%% Demonstrating reading the output files
+[~, out_filename,~] = fileparts(in_file);
+out_filename = sprintf('%s/%s.csv', output, out_filename);
+
+% First read in the column names
+tab = readtable(out_filename);
+column_names = tab.Properties.VariableNames;
+
+all_params  = dlmread(out_filename, ',', 1, 0);
+
+gaze_angle_ids = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'gaze_angle_'));
+
+gaze = all_params(:,gaze_angle_ids);
+
+plot(gaze(:,1), 'DisplayName', 'Left - right');
+hold on;
+plot(gaze(:,2), 'DisplayName', 'Up - down');
+xlabel('Frame') % x-axis label
+ylabel('Angle in radians') % y-axis label
+legend('show');
+hold off;

pkg/OpenFace/matlab_runners/Demos/run_demo_align_size.m

@@ -0,0 +1,47 @@
+% A demo script that demonstrates how to extract aligned faces from a sequence, 
+% also shows how to extract different sized aligned faces
+
+clear
+
+% The location executable will depend on the OS
+if(isunix)
+    executable = '"../../build/bin/FeatureExtraction"';
+else
+    executable = '"../../x64/Release/FeatureExtraction.exe"';
+end
+
+% Input file
+in_file = '../../samples/default.wmv';
+
+% Where to store the output
+output_dir = './processed_features/';
+
+img_sizes = [64, 112, 224];
+
+for s=1:numel(img_sizes)
+    % This will take file after -f and output all the features to directory
+    % after -out_dir, with name after -of
+    command = sprintf('%s -f "%s" -out_dir "%s" -simalign -simsize %d -of sample_%d', executable, in_file, output_dir, img_sizes(s), img_sizes(s) );
+
+    if(isunix)
+        unix(command);
+    else
+        dos(command);
+    end
+
+    %% Output aligned images
+    output_aligned_dir = sprintf('%s/sample_%d_aligned/', output_dir, img_sizes(s));
+    img_files = dir([output_aligned_dir, '/*.bmp']);
+    imgs = cell(numel(img_files), 1);
+    
+    assert(numel(imgs) > 0);
+
+    for i=1:numel(img_files)
+        imgs{i} = imread([ output_aligned_dir, '/', img_files(i).name]);
+    
+        assert(size(imgs{i},1) == img_sizes(s) && size(imgs{i},2) == img_sizes(s));
+        
+        imshow(imgs{i})
+        drawnow
+    end
+end

pkg/OpenFace/matlab_runners/Demos/run_demo_images.m

@@ -0,0 +1,34 @@
+clear
+if(isunix)
+    executable = '"../../build/bin/FaceLandmarkImg"';
+else
+    executable = '"../../x64/Release/FaceLandmarkImg.exe"';
+end
+    
+in_dir  = '../../samples/';
+out_dir = './demo_img/';
+
+model = 'model/main_ceclm_general.txt'; % Trained on in the wild, menpo and multi-pie data (a CE-CLM model)
+
+% Uncomment the below models if you want to try them
+%model = 'model/main_clnf_general.txt'; % Trained on in the wild and multi-pie data (a CLNF model)
+
+%model = 'model/main_clnf_wild.txt'; % Trained on in-the-wild data only
+
+%model = 'model/main_clm_general.txt'; % Trained on in the wild and multi-pie data (less accurate SVR/CLM model)
+%model = 'model/main_clm_wild.txt'; % Trained on in-the-wild
+
+% Load images (-fdir), output images and all the features (-out_dir), use a
+% user specified model (-mloc), and visualize everything (-verbose)
+command = sprintf('%s -fdir "%s" -out_dir "%s" -verbose -mloc "%s" ', executable, in_dir, out_dir, model);
+
+% Demonstrates the multi-hypothesis slow landmark detection (more accurate
+% when dealing with non-frontal faces and less accurate face detections)
+% Comment to skip this functionality
+command = cat(2, command, ' -wild -multi_view 1');
+
+if(isunix)
+    unix(command);
+else
+    dos(command);
+end

pkg/OpenFace/matlab_runners/Demos/run_demo_video_multi.m

@@ -0,0 +1,39 @@
+% A demo how to run a multi-face face tracker
+
+clear;
+
+if(isunix)
+    executable = '"../../build/bin/FaceLandmarkVidMulti"';
+else
+    executable = '"../../x64/Release/FaceLandmarkVidMulti.exe"';
+end
+    
+in_files = dir('../../samples/multi_face.avi');
+
+model = 'model/main_ceclm_general.txt'; % Trained on in the wild, menpo and multi-pie data (a CE-CLM model)
+
+% Uncomment the below models if you want to try them
+%model = 'model/main_clnf_general.txt'; % Trained on in the wild and multi-pie data (a CLNF model)
+
+% Uncomment the below models if you want to try them
+%model = 'model/main_clnf_wild.txt'; % Trained on in-the-wild data only
+
+%model = 'model/main_clm_general.txt'; % Trained on in the wild and multi-pie data (less accurate SVR/CLM model)
+%model = 'model/main_clm_wild.txt'; % Trained on in-the-wild
+
+% Create a command that will run the tracker on set of videos and display the output 
+command = sprintf('%s -mloc "%s" -verbose ', executable, model);
+
+% add all videos to single argument list (so as not to load the model anew
+% for every video)
+for i=1:numel(in_files)
+    inputFile = ['../../samples/', in_files(i).name];        
+    command = cat(2, command, [' -f "' inputFile '" ']);
+end
+
+% Call the executable
+if(isunix)
+    unix(command);
+else
+    dos(command);
+end

pkg/OpenFace/matlab_runners/Demos/run_demo_videos.m

@@ -0,0 +1,40 @@
+% A demo how to run a single-face face tracker
+
+clear
+
+if(isunix)
+    executable = '"../../build/bin/FaceLandmarkVid"';
+else
+    executable = '"../../x64/Release/FaceLandmarkVid.exe"';
+end
+    
+in_files = dir('../../samples/*.wmv');
+in_files = cat(1, in_files, dir('../../samples/*.avi'));
+
+model = 'model/main_ceclm_general.txt'; % Trained on in the wild, menpo and multi-pie data (a CE-CLM model)
+
+% Uncomment the below models if you want to try them
+%model = 'model/main_clnf_general.txt'; % Trained on in the wild and multi-pie data (a CLNF model)
+
+% Uncomment the below models if you want to try them
+%model = 'model/main_clnf_wild.txt'; % Trained on in-the-wild data only
+
+%model = 'model/main_clm_general.txt'; % Trained on in the wild and multi-pie data (less accurate SVR/CLM model)
+%model = 'model/main_clm_wild.txt'; % Trained on in-the-wild
+
+% Create a command that will run the tracker on set of videos and display the output 
+command = sprintf('%s -mloc "%s" ', executable, model);
+
+% add all videos to single argument list by appending -f comments
+% so as not to load the model anew for every video)
+for i=1:numel(in_files)
+    inputFile = ['../../samples/', in_files(i).name];        
+    command = cat(2, command, [' -f "' inputFile '" ']);
+end
+
+% Call the executable
+if(isunix)
+    unix(command);
+else
+    dos(command);
+end

pkg/OpenFace/matlab_runners/Demos/run_test_img_seq.m

@@ -0,0 +1,29 @@
+% A test script on image sequences, making sure grayscale and 16 bit
+% sequences work
+
+clear
+
+% The location executable will depend on the OS
+if(isunix)
+    executable = '"../../build/bin/FeatureExtraction"';
+else
+    executable = '"../../x64/Release/FeatureExtraction.exe"';
+end
+
+% Input file
+in_dirs = {'../../samples/image_sequence',...
+    '../../samples/image_sequence_gray', ...
+    '../../samples/image_sequence_16bit'};
+
+% Where to store the output
+output_dir = './processed_features/';
+
+for i=1:numel(in_dirs)
+    command = sprintf('%s -fdir "%s" -out_dir "%s" -verbose', executable, in_dirs{i}, output_dir);
+
+    if(isunix)
+        unix(command);
+    else
+        dos(command);
+    end
+end