126 lines
3.7 KiB
Matlab
126 lines
3.7 KiB
Matlab
clear
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if(isunix)
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executable = '"../../build/bin/FeatureExtraction"';
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else
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executable = '"../../x64/Release/FeatureExtraction.exe"';
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end
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output = 'yt_features/';
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if(~exist(output, 'file'))
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mkdir(output)
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end
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if(exist([getenv('USERPROFILE') '/Dropbox/AAM/test data/'], 'file'))
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database_root = [getenv('USERPROFILE') '/Dropbox/AAM/test data/'];
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elseif(exist('D:/Dropbox/Dropbox/AAM/test data/', 'file'))
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database_root = 'D:/Dropbox/Dropbox/AAM/test data/';
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elseif(exist('F:/Dropbox/AAM/test data/', 'file'))
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database_root = 'F:/Dropbox/AAM/test data/';
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elseif(exist('/media/tadas/5E08AE0D08ADE3ED/Dropbox/AAM/test data/', 'file'))
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database_root = '/media/tadas/5E08AE0D08ADE3ED/Dropbox/AAM/test data/';
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else
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database_root = '/multicomp/datasets/';
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end
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database_root = [database_root, '/ytceleb/'];
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in_vids = dir([database_root '/*.avi']);
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command = sprintf('%s -2Dfp -out_dir "%s" ', executable, output);
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% add all videos to single argument list (so as not to load the model anew
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% for every video)
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for i=1:numel(in_vids)
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in_file_name = [database_root, '/', in_vids(i).name];
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command = cat(2, command, [' -f "' in_file_name '" ']);
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end
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if(isunix)
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unix(command, '-echo')
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else
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dos(command);
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end
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%%
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output = 'yt_features_clm/';
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if(~exist(output, 'file'))
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mkdir(output)
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end
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command = sprintf('%s -2Dfp -out_dir "%s" -mloc model/main_clm_general.txt ', executable, output);
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% add all videos to single argument list (so as not to load the model anew
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% for every video)
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for i=1:numel(in_vids)
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in_file_name = [database_root, '/', in_vids(i).name];
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command = cat(2, command, [' -f "' in_file_name '"']);
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end
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if(isunix)
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unix(command, '-echo')
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else
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dos(command);
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end
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%% evaluating yt datasets
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d_loc = 'yt_features/';
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d_loc_clm = 'yt_features_clm/';
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files_yt = dir([d_loc, '/*.csv']);
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preds_all = [];
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preds_all_clm = [];
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gts_all = [];
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for i = 1:numel(files_yt)
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[~, name, ~] = fileparts(files_yt(i).name);
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fname = [d_loc, files_yt(i).name];
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if(i == 1)
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% First read in the column names
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tab = readtable(fname);
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column_names = tab.Properties.VariableNames;
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confidence_id = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'confidence'));
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x_ids = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'x_'));
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y_ids = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'y_'));
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end
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all_params = dlmread(fname, ',', 1, 0);
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xs = all_params(:, x_ids);
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ys = all_params(:, y_ids);
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pred_landmarks = zeros([size(xs,2), 2, size(xs,1)]);
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pred_landmarks(:,1,:) = xs';
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pred_landmarks(:,2,:) = ys';
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all_params = dlmread([d_loc_clm, files_yt(i).name], ',', 1, 0);
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xs = all_params(:, x_ids);
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ys = all_params(:, y_ids);
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pred_landmarks_clm = zeros([size(xs,2), 2, size(xs,1)]);
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pred_landmarks_clm(:,1,:) = xs';
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pred_landmarks_clm(:,2,:) = ys';
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load([database_root, name, '.mat']);
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preds_all = cat(3, preds_all, pred_landmarks);
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preds_all_clm = cat(3, preds_all_clm, pred_landmarks_clm);
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gts_all = cat(3, gts_all, labels);
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end
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%%
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[clnf_error, err_pp_clnf] = compute_error( gts_all - 1.5, preds_all);
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[clm_error, err_pp_clm] = compute_error( gts_all - 1.5, preds_all_clm);
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filename = sprintf('results/fps_yt');
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save(filename);
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% Also save them in a reasonable .txt format for easy comparison
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f = fopen('results/fps_yt.txt', 'w');
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fprintf(f, 'Model, mean, median\n');
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fprintf(f, 'OpenFace (CLNF): %.4f, %.4f\n', mean(clnf_error), median(clnf_error));
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fprintf(f, 'CLM: %.4f, %.4f\n', mean(clm_error), median(clm_error));
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fclose(f);
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clear 'f' |