sustaining_gazes/matlab_runners/Feature Point Experiments/run_yt_dataset.m

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2016-04-28 19:40:36 +00:00
clear
executable = '"../../x64/Release/FeatureExtraction.exe"';
output = 'yt_features/';
if(~exist(output, 'file'))
mkdir(output)
end
if(exist([getenv('USERPROFILE') '/Dropbox/AAM/test data/'], 'file'))
database_root = [getenv('USERPROFILE') '/Dropbox/AAM/test data/'];
else
database_root = 'D:/Dropbox/Dropbox/AAM/test data/';
2016-04-28 19:40:36 +00:00
end
database_root = [database_root, '/ytceleb_annotations_CVPR2014/'];
in_vids = dir([database_root '/*.avi']);
command = executable;
command = cat(2, command, ' -no3Dfp -noMparams -noPose -noGaze -noAUs ');
% add all videos to single argument list (so as not to load the model anew
% for every video)
for i=1:numel(in_vids)
[~, name, ~] = fileparts(in_vids(i).name);
% where to output tracking results
outputFile_fp = [output name '_fp.txt'];
in_file_name = [database_root, '/', in_vids(i).name];
command = cat(2, command, [' -f "' in_file_name '" -of "' outputFile_fp '"']);
end
dos(command);
%%
output = 'yt_features_clm/';
if(~exist(output, 'file'))
mkdir(output)
end
command = executable;
command = cat(2, command, ' -mloc model/main_clm_general.txt ');
command = cat(2, command, ' -no3Dfp -noMparams -noPose -noGaze -noAUs ');
% add all videos to single argument list (so as not to load the model anew
% for every video)
for i=1:numel(in_vids)
[~, name, ~] = fileparts(in_vids(i).name);
% where to output tracking results
outputFile_fp = [output name '_fp.txt'];
in_file_name = [database_root, '/', in_vids(i).name];
command = cat(2, command, [' -f "' in_file_name '" -of "' outputFile_fp '"']);
end
dos(command);
%% evaluating yt datasets
d_loc = 'yt_features/';
d_loc_clm = 'yt_features_clm/';
files_yt = dir([d_loc, '/*.txt']);
preds_all = [];
preds_all_clm = [];
gts_all = [];
for i = 1:numel(files_yt)
[~, name, ~] = fileparts(files_yt(i).name);
pred_landmarks = dlmread([d_loc, files_yt(i).name], ',', 1, 0);
pred_landmarks = pred_landmarks(:,5:end);
xs = pred_landmarks(:, 1:end/2);
ys = pred_landmarks(:, end/2+1:end);
pred_landmarks = zeros([size(xs,2), 2, size(xs,1)]);
pred_landmarks(:,1,:) = xs';
pred_landmarks(:,2,:) = ys';
pred_landmarks_clm = dlmread([d_loc_clm, files_yt(i).name], ',', 1, 0);
pred_landmarks_clm = pred_landmarks_clm(:,5:end);
xs = pred_landmarks_clm(:, 1:end/2);
ys = pred_landmarks_clm(:, end/2+1:end);
pred_landmarks_clm = zeros([size(xs,2), 2, size(xs,1)]);
pred_landmarks_clm(:,1,:) = xs';
pred_landmarks_clm(:,2,:) = ys';
load([database_root, name(1:end-3), '.mat']);
preds_all = cat(3, preds_all, pred_landmarks);
preds_all_clm = cat(3, preds_all_clm, pred_landmarks_clm);
gts_all = cat(3, gts_all, labels);
end
%%
[clnf_error, err_pp_clnf] = compute_error( gts_all - 1.5, preds_all);
[clm_error, err_pp_clm] = compute_error( gts_all - 1.5, preds_all_clm);
filename = sprintf('results/fps_yt');
save(filename);
% Also save them in a reasonable .txt format for easy comparison
f = fopen('results/fps_yt.txt', 'w');
fprintf(f, 'Model, mean, median\n');
fprintf(f, 'OpenFace (CLNF): %.4f, %.4f\n', mean(clnf_error), median(clnf_error));
fprintf(f, 'CLM: %.4f, %.4f\n', mean(clm_error), median(clm_error));
fclose(f);
clear 'f'