open source pkg v1
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function net = initializeFaceCNN_simple_5(num_bins)
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f=1/100 ;
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net.layers = {} ;
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net.layers{end+1} = struct('type', 'conv', ...
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'weights', {{f*randn(9,9,1,10, 'single'), zeros(1, 10, 'single')}}, ...
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'stride', 1, ...
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'pad', 0) ;
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net.layers{end+1} = struct('type', 'relu') ;
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net.layers{end+1} = struct('type', 'pool', ...
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'method', 'max', ...
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'pool', [2 2], ...
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'stride', 2, ...
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'pad', 0) ;
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net.layers{end+1} = struct('type', 'conv', ...
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'weights', {{f*randn(7,7,10,10, 'single'), zeros(1,10,'single')}}, ...
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'stride', 1, ...
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'pad', 0) ;
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net.layers{end+1} = struct('type', 'relu') ;
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net.layers{end+1} = struct('type', 'pool', ...
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'method', 'max', ...
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'pool', [2 2], ...
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'stride', 2, ...
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'pad', 0) ;
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% This is basically an FC layer
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net.layers{end+1} = struct('type', 'conv', ...
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'weights', {{f*randn(10,10,10,50, 'single'), zeros(1,50,'single')}}, ...
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'stride', 1, ...
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'pad', 0) ;
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net.layers{end+1} = struct('type', 'relu') ;
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net.layers{end+1} = struct('type', 'conv', ...
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'weights', {{f*randn(1,1,50,num_bins, 'single'), zeros(1,num_bins,'single')}}, ...
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'stride', 1, ...
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'pad', 0) ;
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net.layers{end+1} = struct('type', 'softmaxloss') ;
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net = vl_simplenn_tidy(net) ;
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