140 lines
3.6 KiB
Matlab
140 lines
3.6 KiB
Matlab
function [ err_outline, err_no_outline ] = Run_OF_on_images(output_loc, database_root, varargin)
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dataset_dirs = {};
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if(any(strcmp(varargin, 'use_afw')))
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afw_loc = [database_root '/AFW/'];
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dataset_dirs = cat(1, dataset_dirs, afw_loc);
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end
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if(any(strcmp(varargin, 'use_lfpw')))
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lfpw_loc = [database_root 'lfpw/testset/'];
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dataset_dirs = cat(1, dataset_dirs, lfpw_loc);
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end
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if(any(strcmp(varargin, 'use_ibug')))
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ibug_loc = [database_root 'ibug/'];
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dataset_dirs = cat(1, dataset_dirs, ibug_loc);
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end
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if(any(strcmp(varargin, 'use_helen')))
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helen_loc = [database_root '/helen/testset/'];
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dataset_dirs = cat(1, dataset_dirs, helen_loc);
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end
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if(any(strcmp(varargin, 'verbose')))
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verbose = true;
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else
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verbose = false;
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end
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if(isunix)
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executable = '"../../build/bin/FaceLandmarkImg"';
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else
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executable = '"../../x64/Release/FaceLandmarkImg.exe"';
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end
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if(any(strcmp(varargin, 'model')))
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model = varargin{find(strcmp(varargin, 'model')) + 1};
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else
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% the default model is the 68 point in the wild one
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model = '"model/main_wild.txt"';
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end
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if(any(strcmp(varargin, 'multi_view')))
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multi_view = varargin{find(strcmp(varargin, 'multi_view')) + 1};
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else
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multi_view = 0;
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end
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command = sprintf('%s -mloc %s -multi_view %s -2Dfp ', executable, model, num2str(multi_view));
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tic
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for i=1:numel(dataset_dirs)
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command_c = sprintf('%s -fdir "%s" -bboxdir "%s" -out_dir "%s" -wild ',...
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command, dataset_dirs{i}, dataset_dirs{i}, output_loc);
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if(isunix)
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unix(command_c, '-echo');
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else
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dos(command_c);
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end
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end
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toc
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%%
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% Extract the error sizes
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dirs = {[database_root '/AFW/'];
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[database_root '/ibug/'];
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[database_root '/helen/testset/'];
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[database_root 'lfpw/testset/'];};
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landmark_dets = dir([output_loc '/*.csv']);
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landmark_det_dir = [output_loc '/'];
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num_imgs = size(landmark_dets,1);
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labels = zeros(68,2,num_imgs);
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shapes = zeros(68,2,num_imgs);
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curr = 0;
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% work out which columns in the csv file are relevant
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tab = readtable([landmark_det_dir, landmark_dets(1).name]);
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column_names = tab.Properties.VariableNames;
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landmark_inds_x = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'x_'));
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landmark_inds_y = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'y_'));
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for i=1:numel(dirs)
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gt_labels = dir([dirs{i}, '*.pts']);
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for g=1:numel(gt_labels)
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curr = curr+1;
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gt_landmarks = dlmread([dirs{i}, gt_labels(g).name], ' ', 'A4..B71');
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[~, name, ~] = fileparts(gt_labels(g).name);
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% find the corresponding detection
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all_params = dlmread([landmark_det_dir, name, '.csv'], ',', 1, 0);
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landmark_det = [all_params(landmark_inds_x); all_params(landmark_inds_y)]';
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labels(:,:,curr) = gt_landmarks;
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if(size(landmark_det,1) == 66)
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inds_66 = [[1:60],[62:64],[66:68]];
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shapes(inds_66,:,curr) = landmark_det;
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else
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shapes(:,:,curr) = landmark_det;
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end
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end
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end
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% Convert to correct format, so as to have same feature points in ground
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% truth and detections
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if(size(shapes,2) == 66 && size(labels,2) == 68)
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inds_66 = [[1:60],[62:64],[66:68]];
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labels = labels(inds_66,:,:);
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shapes = shapes(inds_66,:,:);
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end
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% Center the pixel, and convert to OCV format
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labels = labels - 1.5;
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err_outline = compute_error(labels, shapes);
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labels_no_out = labels(18:end,:,:);
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shapes_no_out = shapes(18:end,:,:);
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err_no_outline = compute_error(labels_no_out, shapes_no_out);
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%%
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save([output_loc, 'res.mat'], 'labels', 'shapes', 'err_outline', 'err_no_outline');
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end |