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OpenFace/matlab_version/experiments_menpo/Script_CECLM_menpo_valid.m
2017-04-10 09:52:14 -04:00

157 lines
4.4 KiB
Matlab

function Script_CECLM_menpo_valid()
addpath('../PDM_helpers/');
addpath('../fitting/normxcorr2_mex_ALL');
addpath('../fitting/');
addpath('../CCNF/');
addpath('../models/');
[images, detections, labels] = Collect_valid_imgs('D:\Datasets\menpo/');
%% loading the patch experts
clmParams = struct;
clmParams.window_size = [25,25; 23,23; 21,21; 21,21];
clmParams.numPatchIters = size(clmParams.window_size,1);
[patches] = Load_DCLM_Patch_Experts( '../models/cen/', 'cen_patches_*_menpo.mat', [], [], clmParams);
%% Fitting the model to the provided image
output_root = './menpo_fit_ceclm/';
% the default PDM to use
pdmLoc = ['../models/pdm/pdm_68_aligned_menpo.mat'];
load(pdmLoc);
pdm = struct;
pdm.M = double(M);
pdm.E = double(E);
pdm.V = double(V);
clmParams.regFactor = 0.9 * [35, 27, 20, 20];
clmParams.sigmaMeanShift = 1.5 * [1.25, 1.375, 1.5, 1.5];
clmParams.tikhonov_factor = [2.5, 5, 7.5, 7.5];
clmParams.startScale = 1;
clmParams.num_RLMS_iter = 10;
clmParams.fTol = 0.01;
clmParams.useMultiScale = true;
clmParams.use_multi_modal = 1;
clmParams.multi_modal_types = patches(1).multi_modal_types;
clmParams.numPatchIters = 4;
% for recording purposes
experiment.params = clmParams;
num_points = numel(M)/3;
shapes_all = cell(numel(images), 1);
labels_all = cell(numel(images), 1);
lhoods = zeros(numel(images),1);
all_lmark_lhoods = zeros(num_points, numel(images));
all_views_used = zeros(numel(images),1);
% Use the multi-hypothesis model, as bounding box tells nothing about
% orientation
multi_view = true;
verbose = false;
tic
for i=29:numel(images)
image = imread(images(i).img);
image_orig = image;
if(size(image,3) == 3)
image = rgb2gray(image);
end
bbox = squeeze(detections(i,:));
% have a multi-view version
if(multi_view)
views = [0,0,0; 0,-70,40; 0,70,-40; 0,-30,0; 0,-60,0; 0,-90,0; 0,30,0; 0,60,0; 0,90,0; 0,0,30; 0,0,-30;];
views = views * pi/180;
shapes = zeros(num_points, 2, size(views,1));
ls = zeros(size(views,1),1);
lmark_lhoods = zeros(num_points,size(views,1));
views_used = zeros(size(views,1),1);
globals = zeros(size(views,1),6);
% Find the best orientation
for v = 1:size(views,1)
[shapes(:,:,v),globals(v,:),~,ls(v),lmark_lhoods(:,v),views_used(v)] = Fitting_from_bb(image, [], bbox, pdm, patches, clmParams, 'orientation', views(v,:));
end
[lhood, v_ind] = max(ls);
lmark_lhood = lmark_lhoods(:,v_ind);
glob = globals(v_ind,:);
shape = shapes(:,:,v_ind);
view_used = views_used(v_ind);
else
[shape,~,~,lhood,lmark_lhood,view_used] = Fitting_from_bb(image, [], bbox, pdm, patches, clmParams);
end
all_lmark_lhoods(:,i) = lmark_lhood;
all_views_used(i) = view_used;
shapes_all{i} = shape;
labels_all{i} = labels{i};
if(mod(i, 200)==0)
fprintf('%d done\n', i );
end
lhoods(i) = lhood;
if(verbose)
actualShape = labels{i};
f = figure('visible','off');
% f = figure;
try
if(max(image_orig(:)) > 1)
imshow(double(image_orig)/255, 'Border', 'tight');
else
imshow(double(image_orig), 'Border', 'tight');
end
axis equal;
hold on;
v_points = logical(patches(1).visibilities(view_used,:))';
plot(shape(v_points,1), shape(v_points,2),'.r','MarkerSize',20);
plot(shape(v_points,1), shape(v_points,2),'.b','MarkerSize',10);
% print(f, '-r80', '-dpng', sprintf('%s/%s%d.png', output_root, 'fit', i));
print(f, '-djpeg', sprintf('%s/%s%d.jpg', output_root, 'fit', i));
% close(f);
hold off;
drawnow expose
close(f);
catch warn
end
end
end
toc
experiment.lhoods = lhoods;
experiment.shapes = shapes_all;
experiment.labels = labels_all;
experiment.all_lmark_lhoods = all_lmark_lhoods;
experiment.all_views_used = all_views_used;
% save the experiment
if(~exist('experiments', 'var'))
experiments = experiment;
else
experiments = cat(1, experiments, experiment);
end
output_results = 'results/results_ceclm_valid.mat';
save(output_results, 'experiments');
end