experiments.m

function experiments()
% EXPERIMENTS   Run image classification experiments
%    The experimens download a number of benchmark datasets in the
%    'data/' subfolder. Make sure that there are several GBs of
%    space available.
%
%    By default, experiments run with a lite option turned on. This
%    quickly runs all of them on tiny subsets of the actual data.
%    This is used only for testing; to run the actual experiments,
%    set the lite variable to false.
%
%    Running all the experiments is a slow process. Using parallel
%    MATLAB and several corkes/machiens is suggested.

% Author: Andrea Vedaldi

% Copyright (C) 2013 Andrea Vedaldi
% All rights reserved.
%
% This file is part of the VLFeat library and is made available under
% the terms of the BSD license (see the COPYING file).
lite = false;
clear ex ;
if lite, tag = 'lite' ;
else, tag = 'ex' ; end
MDII_numTrain=3061;
MDII_numTest=3061;
trainType='rgb'
testType='thr'

% vlad
ex(1).prefix = 'vlad-aug' ;
ex(1).trainOpts = { 'C', 10} ;
ex(1).datasets = {'MDII'} ;
ex(1).seed = 1 ;
ex(1).opts = {...
  'type', 'vlad', ...
  'numWords', 1024, ...
  'layouts', {'1x1'}, ...
  'geometricExtension', 'xy', ...
  'numPcaDimensions', 100, ...
  'whitening', true, ...
  'whiteningRegul', 0.01, ...
  'renormalize', true, ...
  'extractorFn', @(x) getDenseSIFT(x, ...
                                   'step', 4, ...
                                   'scales', 2.^(1:-.5:-3))};


% bovw
ex(2).prefix = 'bovw-aug' ;
ex(2).trainOpts = { 'C', 10} ;
ex(2).datasets = {'MDII'} ;
ex(2).seed = 1 ;
ex(2).opts = {...
  'type', 'bovw', ...
  'numWords', 1024, ...
  'layouts', {'1x1'}, ...
  'geometricExtension', 'xy', ...
  'numPcaDimensions', 100, ...
  'whitening', true, ...
  'whiteningRegul', 0.01, ...
  'renormalize', true, ...
  'extractorFn', @(x) getDenseSIFT(x, ...
                                   'step', 4, ...
                                   'scales', 2.^(1:-.5:-3))};

                               


for i=1:2
  for j=1:numel(ex(i).datasets)
    dataset = ex(i).datasets{j} ;
    if ~isfield(ex(i), 'trainOpts') || ~iscell(ex(i).trainOpts)
      ex(i).trainOpts = {} ;
    end
    traintestMDII(...
      trainType, testType, ... 
      MDII_numTrain, MDII_numTest, ...
      'prefix', [tag '-' dataset '-' ex(i).prefix], ...
      'seed', ex(i).seed, ...
      'dataset', char(dataset), ...
      'datasetDir', fullfile('data', dataset), ...
      'lite', lite, ...
      ex(i).trainOpts{:}, ...
      'encoderParams', ex(i).opts) ;
  end
end