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apply_subcat_detector_to_AFW.m
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apply_subcat_detector_to_AFW.m
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function apply_subcat_detector_to_AFW(dataDir, dataOutputDir, D)
% dataDir - Path of the directory with the prepared face databases data.
% dataOutputDir - Path to store trained detector and detection results in.
if (nargin < 4)
RESAMPLING = 1;
end
mkdir(dataOutputDir);
exp_name='AFLW';
% Size of the search window
MIN_HEIGHT = 40;
BEST_ASPECT_RATIO = 1;
BEST_PADDING_RATIO = 1/8;
% For testing
OVERLAPING_TP = 0.5;
% Our parameters
imgTestDir = fullfile(dataDir, 'afw_pdollar_format/images');
lbsTestDir = fullfile(dataDir, 'afw_pdollar_format/annotations');
pLoad={'lbls',{'Face'},'ilbls',{'DontCare'}};
pLoad = {pLoad{:} 'hRng',[round(MIN_HEIGHT*0.8) inf]};
pLoad = {pLoad{:} 'format', 0};
num_classes = 5+1; % 5 orientations + background
DETECTOR_FILE_PREFIX = sprintf('SUBCAT_D_%d_', D);
%--------------------------------------------------------------------------
% Now, load the already trained BAdaCost based detector
%--------------------------------------------------------------------------
detectorFile = fullfile(dataOutputDir, [DETECTOR_FILE_PREFIX 'Detector.mat']);
%--------------------------------------------------------------------------
% Load the trained detector
%--------------------------------------------------------------------------
detector = load(detectorFile);
detector = detector.detector;
%detectorBAK = detector;
% detector.opts.pNms.type = 'max';
% detector.opts.pNms.overlap = 0.5;
% detector.opts.pNms.ovrDnm = 'min';
for i=1:length(detector)
detector{i}.opts.pPyramid.nOctUp=0; % Not needed in AFW
end
detectorPrefix_AFW = fullfile(dataOutputDir, sprintf('AFW_D_%d_', D));
detectorFile_AFW = [detectorPrefix_AFW 'Detector.mat'];
save(detectorFile_AFW, 'detector');
%detector = detectorBAK;
%--------------------------------------------------------------------------
% test detector and plot roc (see acfTest)
%--------------------------------------------------------------------------
pLoad2=pLoad;
if iscell(pLoad)
index = find(strcmp(pLoad2, 'format'));
if ~isempty(index)
pLoad2{index+1} = 0; % Format 0 is all data
end
elseif isstruct(pLoad2)
if isfield(pLoad2, 'format')
pLoad2.format = 0; % Format 0 is all data.
end
end
pLoadTest = {pLoad2{:}};
[miss,roc,gt,dt]=acfTest('name',detectorPrefix_AFW,...
'imgDir',imgTestDir,...
'gtDir',lbsTestDir,...
'pLoad',pLoadTest,...
'show',1, ...
'thr', OVERLAPING_TP); % Overlaping threshold for a BoundingBox as TP
% From now on we use AFW dataset to test ...
exp_name = 'AFW'
save(fullfile(dataOutputDir, [exp_name '_TEST_RESULTS.mat']), 'miss', 'roc', 'gt', 'dt');
h = figure;
ref = 10.^(-2:.25:0);
lims = [3.1e-3 1e1 .05 1];
color = {'r', 'g', 'b', 'k', 'm', 'c', 'y'};
lineSt = {'-', ':', '--', '.', '-', ':', '--'};
%[fp,tp,score,miss_test] = bbGt('compRoc',gt,dt,1,ref);
[fp,tp,~,miss_test] = bbGt('compRoc',gt,dt,1,ref);
[hs,~,~] =plotRoc([fp tp],'logx',1,'logy',0, 'xLbl', 'fppi',...
'lims', lims, 'color', color{1}, 'lineSt', lineSt{1}, 'smooth', 1, 'fpTarget', ref);
legend_string = sprintf('asp.ratio=%2.2f, pad.ratio=%2.2f, recall (at 1FFPI)=%.2f%%', ...
BEST_ASPECT_RATIO, BEST_PADDING_RATIO, ...
miss_test(end)*100);
legend(hs, legend_string, 'Location', 'Best');
hold off;
saveas(gcf, fullfile(dataOutputDir, [exp_name '_Roc.eps']), 'epsc');
saveas(gcf, fullfile(dataOutputDir, [exp_name '_Roc.png']), 'png');
h = figure;
ref = 10.^(-2:.25:0);
lims = [3.1e-3 1e1 .05 1];
color = {'r', 'g', 'b', 'k', 'm', 'c', 'y'};
lineSt = {'-', ':', '--', '.', '-', ':', '--'};
%[fp,tp,score,miss_test] = bbGt('compRoc',gt,dt,1,ref);
[fp,tp,~,miss_test] = bbGt('compRoc',gt,dt,1,ref);
[hs,~,~] = plotRoc([fp tp],'logx',1,'logy',0, 'xLbl', 'fppi',...
'lims', lims, 'color', color{1}, 'lineSt', lineSt{1}, 'smooth', 1, 'fpTarget', ref);
legend_string = sprintf('asp.ratio=%2.2f, pad.ratio=%2.2f, recall (at 0.1 FFPI)=%.2f%%', ...
BEST_ASPECT_RATIO, BEST_PADDING_RATIO, ...
miss_test(5)*100);
legend(hs, legend_string, 'Location', 'Best');
hold off;
saveas(gcf, fullfile(dataOutputDir, [exp_name '_Roc2.eps']), 'epsc');
saveas(gcf, fullfile(dataOutputDir, [exp_name '_Roc2.png']), 'png');
%--------------------------------------------------------------------------
% Plot results over images.
%--------------------------------------------------------------------------
figure;
IMG_RESULTS_PATH = fullfile(dataOutputDir, 'IMG_RESULTS_AFW_FACES');
mkdir(IMG_RESULTS_PATH);
LABELS_RESULTS_PATH = fullfile(dataOutputDir, 'LABELS_RESULTS_AFW_FACES');
mkdir(LABELS_RESULTS_PATH);
imgNms = bbGt('getFiles',{imgTestDir});
if (~exist('NICE_VISUALISATION', 'var'))
NICE_VISUALISATION = false;
end
if (~exist('NICE_VISUALISATION_SCORE_THRESHOLD', 'var'))
NICE_VISUALISATION = false;
end
fid = fopen(fullfile(dataOutputDir, 'AFW_FACES_COMPATIBLE_Dets.txt'), 'w');
for i=1:length(imgNms)
file_name = strsplit(imgNms{i}, '/');
file_name = file_name{end};
[~,name,~]=fileparts(file_name);
I = imread(fullfile(imgTestDir, file_name));
dt_i = dt{i};
gt_i = gt{i};
% dt_i(:,6) = ones(size(dt_i, 1), 1);
% dt_i(:,7) = dt_i(:,7)-ones(size(dt_i, 1), 1);
if NICE_VISUALISATION
% Show results with nice visualization (removed score < NICE_VISUALIZATION_SCORE_THRESHOLD detections)
showResOpts ={'evShow',0,'gtShow',0, 'dtShow',1, 'isMulticlass', 0, 'dtLs', '-'};
dt_i_nice = dt_i(dt_i(:,5)>=NICE_VISUALISATION_SCORE_THRESHOLD, :);
%[rows, cols] = size(I);
%[hs,hImg] = bbGt('showRes', I, gt_i, dt_i_nice, showResOpts); % multiClass = 1
bbGt('showRes', I, gt_i, dt_i_nice, showResOpts); % multiClass = 1
saveas(gcf, fullfile(IMG_RESULTS_PATH, ['NICE_VISUALISATION_' file_name '.png']), 'png');
else
% Show full results and comparison with ground thruth
showResOpts ={'evShow',1,'gtShow',1, 'dtShow',1, 'isMulticlass', 0};
%[hs,hImg] = bbGt('showRes', I, gt_i, dt_i, showResOpts); % multiClass = 1
bbGt('showRes', I, gt_i, dt_i, showResOpts); % multiClass = 1
saveas(gcf, fullfile(IMG_RESULTS_PATH, [file_name '.png']), 'png');
end
for j=1:size(dt_i,1)
x1 = dt_i(j,1)-1;
y1 = dt_i(j,2)-1;
x2 = x1 + dt_i(j,3) - 1;
y2 = y1 + dt_i(j,4) - 1;
fprintf(fid, '%s %f %f %f %f %f\n', name, dt_i(j,5), x1, y1, x2, y2);
end;
end
fclose(fid);