99 lines
3.1 KiB
Matlab
99 lines
3.1 KiB
Matlab
clear
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addpath('../PDM_helpers/');
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addpath(genpath('../fitting/'));
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addpath('../models/');
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addpath(genpath('../face_detection'));
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addpath('../CCNF/');
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%% loading the patch experts
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[clmParams, pdm] = Load_CLM_params_wild();
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% An accurate CCNF (or CLNF) model
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[patches] = Load_Patch_Experts( '../models/general/', 'ccnf_patches_*_general.mat', [], [], clmParams);
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% A simpler (but less accurate SVR)
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% [patches] = Load_Patch_Experts( '../models/general/', 'svr_patches_*_general.mat', [], [], clmParams);
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clmParams.multi_modal_types = patches(1).multi_modal_types;
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%%
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root_dir = '../../samples/';
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images = dir([root_dir, '*.jpg']);
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verbose = true;
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for img=1:numel(images)
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image_orig = imread([root_dir images(img).name]);
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% First attempt to use the Matlab one (fastest but not as accurate, if not present use yu et al.)
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[bboxs, det_shapes] = detect_faces(image_orig, {'cascade', 'yu'});
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% Zhu and Ramanan and Yu et al. are slower, but also more accurate
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% and can be used when vision toolbox is unavailable
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% [bboxs, det_shapes] = detect_faces(image_orig, {'yu', 'zhu'});
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% The complete set that tries all three detectors starting with fastest
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% and moving onto slower ones if fastest can't detect anything
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% [bboxs, det_shapes] = detect_faces(image_orig, {'cascade', 'yu', 'zhu'});
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if(size(image_orig,3) == 3)
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image = rgb2gray(image_orig);
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end
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%%
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if(verbose)
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f = figure;
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if(max(image(:)) > 1)
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imshow(double(image_orig)/255, 'Border', 'tight');
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else
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imshow(double(image_orig), 'Border', 'tight');
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end
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axis equal;
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hold on;
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end
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for i=1:size(bboxs,2)
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% Convert from the initial detected shape to CLM model parameters,
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% if shape is available
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bbox = bboxs(:,i);
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if(~isempty(det_shapes))
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shape = det_shapes(:,:,i);
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inds = [1:60,62:64,66:68];
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M = pdm.M([inds, inds+68, inds+68*2]);
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E = pdm.E;
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V = pdm.V([inds, inds+68, inds+68*2],:);
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[ a, R, T, ~, params, err, shapeOrtho] = fit_PDM_ortho_proj_to_2D(M, E, V, shape);
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g_param = [a; Rot2Euler(R)'; T];
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l_param = params;
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% Use the initial global and local params for clm fitting in the image
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[shape,~,~,lhood,lmark_lhood,view_used] = Fitting_from_bb(image, [], bbox, pdm, patches, clmParams, 'gparam', g_param, 'lparam', l_param);
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else
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[shape,~,~,lhood,lmark_lhood,view_used] = Fitting_from_bb(image, [], bbox, pdm, patches, clmParams);
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end
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% shape correction for matlab format
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shape = shape + 1;
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if(verbose)
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% valid points to draw (not to draw self-occluded ones)
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v_points = logical(patches(1).visibilities(view_used,:));
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try
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plot(shape(v_points,1), shape(v_points',2),'.r','MarkerSize',20);
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plot(shape(v_points,1), shape(v_points',2),'.b','MarkerSize',10);
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catch warn
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end
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end
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end
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hold off;
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end |