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Cleaning up 300W results and JANUS ones.
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@@ -13,7 +13,7 @@ clmParams = struct;
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clmParams.window_size = [25,25; 23,23; 21,21];
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clmParams.numPatchIters = size(clmParams.window_size,1);
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[patches] = Load_Patch_Experts( '../models/general/', 'ccnf_patches_*_general.mat', [], [], clmParams);
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[patches] = Load_Patch_Experts( '../models/wild/', 'ccnf_patches_*_wild.mat', [], [], clmParams);
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%% Fitting the model to the provided image
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@@ -106,9 +106,9 @@ for i=1:numel(images)
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if(a > 0.9)
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g_param = [a; Rot2Euler(R)'; T];
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bbox = [min(shape_inner(:,1)), min(shape_inner(:,2)), max(shape_inner(:,1)), max(shape_inner(:,2))];
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bbox_2 = [min(shape_inner(:,1)), min(shape_inner(:,2)), max(shape_inner(:,1)), max(shape_inner(:,2))];
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[shape_inner] = Fitting_from_bb(image, [], bbox, pdm_inner, patches_inner, clmParams_inner, 'gparam', g_param, 'lparam', l_params);
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[shape_inner] = Fitting_from_bb(image, [], bbox_2, pdm_inner, patches_inner, clmParams_inner, 'gparam', g_param, 'lparam', l_params);
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% Now after detections incorporate the eyes back
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% into the face model
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@@ -151,7 +151,7 @@ fprintf('Done: mean normed error %.3f median normed error %.4f\n', ...
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mean(experiment.errors_normed), median(experiment.errors_normed));
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%%
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output_results = 'results/results_wild_clnf_general.mat';
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output_results = 'results/results_clnf_wild.mat';
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save(output_results, 'experiment');
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end
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