mirror of
https://gitcode.com/gh_mirrors/ope/OpenFace.git
synced 2026-05-14 19:27:56 +00:00
117 lines
3.1 KiB
Matlab
117 lines
3.1 KiB
Matlab
function Script_CLNF_wild()
|
|
|
|
addpath(genpath('../'));
|
|
|
|
% Replace this with the location of the IJB-FL data location
|
|
root_test_data = 'D:/Datasets/janus_labeled';
|
|
[images, detections, labels] = Collect_JANUS_imgs(root_test_data);
|
|
|
|
%% 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_Patch_Experts( '../models/wild/', 'ccnf_patches_*_wild.mat', [], [], clmParams);
|
|
|
|
%% Fitting the model to the provided image
|
|
|
|
% the default PDM to use
|
|
pdmLoc = ['../models/pdm/pdm_68_aligned_wild.mat'];
|
|
|
|
load(pdmLoc);
|
|
|
|
pdm = struct;
|
|
pdm.M = double(M);
|
|
pdm.E = double(E);
|
|
pdm.V = double(V);
|
|
|
|
clmParams.regFactor = [35, 27, 20, 20];
|
|
clmParams.sigmaMeanShift = [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;
|
|
|
|
% for recording purposes
|
|
experiment.params = clmParams;
|
|
|
|
num_points = numel(M)/3;
|
|
|
|
shapes_all = zeros(size(labels,2),size(labels,3), size(labels,1));
|
|
labels_all = zeros(size(labels,2),size(labels,3), size(labels,1));
|
|
lhoods = zeros(numel(images),1);
|
|
|
|
% Use the multi-hypothesis model, as bounding box tells nothing about
|
|
% orientation
|
|
multi_view = true;
|
|
verbose = false; % set to true to visualise the fitting
|
|
|
|
tic
|
|
for i=1:numel(images)
|
|
|
|
image = imread(images(i).img);
|
|
image_orig = image;
|
|
|
|
if(size(image,3) == 3)
|
|
image = rgb2gray(image);
|
|
end
|
|
|
|
bbox = detections(i,:);
|
|
|
|
% have a multi-view version
|
|
if(multi_view)
|
|
|
|
views = [0,0,0; 0,-30,0; 0,30,0; 0,-55,0; 0,55,0; 0,0,30; 0,0,-30; 0,-90,0; 0,90,0; 0,-70,40; 0,70,-40];
|
|
views = views * pi/180;
|
|
|
|
shapes = zeros(num_points, 2, size(views,1));
|
|
ls = zeros(size(views,1),1);
|
|
|
|
% Find the best orientation
|
|
for v = 1:size(views,1)
|
|
[shapes(:,:,v),~,~,ls(v)] = Fitting_from_bb(image, [], bbox, pdm, patches, clmParams, 'orientation', views(v,:));
|
|
end
|
|
|
|
[lhood, v_ind] = max(ls);
|
|
shape = shapes(:,:,v_ind);
|
|
|
|
else
|
|
[shape,~,~,lhood] = Fitting_from_bb(image, [], bbox, pdm, patches, clmParams);
|
|
end
|
|
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)
|
|
v_points = sum(squeeze(labels(i,:,:)),2) > 0;
|
|
DrawFaceOnFig(image_orig, shape, bbox, v_points);
|
|
end
|
|
|
|
end
|
|
toc
|
|
|
|
experiment.errors_normed = compute_error(labels_all, shapes_all - 1.0);
|
|
experiment.lhoods = lhoods;
|
|
experiment.shapes = shapes_all;
|
|
experiment.labels = labels_all;
|
|
|
|
fprintf('Done: mean normed error %.3f median normed error %.4f\n', ...
|
|
mean(experiment.errors_normed), median(experiment.errors_normed));
|
|
|
|
%%
|
|
output_results = 'results/results_clnf_wild.mat';
|
|
save(output_results, 'experiment');
|
|
|
|
end
|