Same fix for multi-face case.
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2 changed files with 16 additions and 24 deletions
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@ -1,3 +1,5 @@
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% A demo how to run a multi-face face tracker
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clear;
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if(isunix)
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@ -13,37 +15,27 @@ if(~exist(output, 'file'))
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end
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in_files = dir('../../samples/multi_face.avi');
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% some parameters
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verbose = true;
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% Trained on in the wild and multi-pie data (less accurate CLM model)
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%model = 'model/main_clm_general.txt';
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% Trained on in-the-wild
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%model = 'model/main_clm_wild.txt';
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model = 'model/main_clnf_general.txt'; % Trained on in the wild and multi-pie data (a CLNF model)
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% Trained on in the wild and multi-pie data (more accurate CLNF model)
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model = 'model/main_clnf_general.txt';
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% Trained on in-the-wild
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%model = 'model/main_clnf_wild.txt';
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% Uncomment the below models if you want to try them
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%model = 'model/main_clnf_wild.txt'; % Trained on in-the-wild data only
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%model = 'model/main_clm_general.txt'; % Trained on in the wild and multi-pie data (less accurate SVR/CLM model)
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%model = 'model/main_clm_wild.txt'; % Trained on in-the-wild
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% Create a command that will run the tracker on set of videos,
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% and visualize the output (-verbose)
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command = sprintf('%s -mloc "%s" -verbose', executable, model);
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command = executable;
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command = cat(2, command, [' -mloc "', model, '"']);
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% add all videos to single argument list (so as not to load the model anew
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% for every video)
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for i=1:numel(in_files)
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inputFile = ['../../samples/', in_files(i).name];
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[~, name, ~] = fileparts(inputFile);
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command = cat(2, command, [' -f "' inputFile '" ']);
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if(verbose)
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outputVideo = ['"' output name '.avi' '"'];
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command = cat(2, command, [' -ov ' outputVideo]);
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end
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end
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% Call the executable
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if(isunix)
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unix(command);
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else
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@ -1,3 +1,5 @@
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% A demo how to run a single-face face tracker
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clear
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if(isunix)
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@ -6,8 +8,6 @@ else
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executable = '"../../x64/Release/FaceLandmarkVid.exe"';
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end
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output = './demo_vids/';
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in_files = dir('../../samples/*.wmv');
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in_files = cat(1, in_files, dir('../../samples/*.avi'));
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