93 lines
2.5 KiB
Matlab
93 lines
2.5 KiB
Matlab
clear
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addpath(genpath('helpers/'));
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find_SEMAINE;
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out_loc = './out_SEMAINE/';
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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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%%
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parfor f1=1:numel(devel_recs)
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if(isdir([SEMAINE_dir, devel_recs{f1}]))
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vid_file = dir([SEMAINE_dir, devel_recs{f1}, '/*.avi']);
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f1_dir = devel_recs{f1};
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curr_vid = [SEMAINE_dir, f1_dir, '/', vid_file.name];
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command = sprintf('%s -aus -f "%s" -out_dir "%s" ', executable, curr_vid, out_loc);
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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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end
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end
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%% Actual model evaluation
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[ labels, valid_ids, vid_ids, vid_names ] = extract_SEMAINE_labels(SEMAINE_dir, devel_recs, aus_SEMAINE);
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labels_gt = cat(1, labels{:});
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%% Identifying which column IDs correspond to which AU
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tab = readtable([out_loc, vid_names{1}, '.csv']);
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column_names = tab.Properties.VariableNames;
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% As there are both classes and intensities list and evaluate both of them
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aus_pred_class = [];
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inds_class_in_file = [];
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for c=1:numel(column_names)
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if(strfind(column_names{c}, '_c') > 0)
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aus_pred_class = cat(1, aus_pred_class, int32(str2num(column_names{c}(3:end-2))));
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inds_class_in_file = cat(1, inds_class_in_file, c);
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end
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end
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%%
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inds_au_class = zeros(size(aus_SEMAINE));
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for ind=1:numel(aus_SEMAINE)
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if(~isempty(find(aus_pred_class==aus_SEMAINE(ind), 1)))
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inds_au_class(ind) = inds_class_in_file(aus_pred_class==aus_SEMAINE(ind));
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end
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end
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preds_all = [];
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for i=1:numel(vid_names)
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fname = [out_loc, vid_names{i}, '.csv'];
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preds = dlmread(fname, ',', 1, 0);
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preds_all = cat(1, preds_all, preds(vid_ids(i,1):vid_ids(i,2) - 1, :));
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end
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%%
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f = fopen('results/SEMAINE_valid_res.txt', 'w');
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f1s = zeros(1, numel(aus_SEMAINE));
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for au = 1:numel(aus_SEMAINE)
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if(inds_au_class(au) ~= 0)
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tp = sum(labels_gt(:,au) == 1 & preds_all(:, inds_au_class(au)) == 1);
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fp = sum(labels_gt(:,au) == 0 & preds_all(:, inds_au_class(au)) == 1);
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fn = sum(labels_gt(:,au) == 1 & preds_all(:, inds_au_class(au)) == 0);
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tn = sum(labels_gt(:,au) == 0 & preds_all(:, inds_au_class(au)) == 0);
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precision = tp./(tp+fp);
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recall = tp./(tp+fn);
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f1 = 2 * precision .* recall ./ (precision + recall);
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f1s(au) = f1;
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fprintf(f, 'AU%d class, Precision - %.3f, Recall - %.3f, F1 - %.3f\n', aus_SEMAINE(au), precision, recall, f1);
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end
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end
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fclose(f); |