product quantization SDC算法在Windows下的实现

% Generate or load an evaluation set (query+learn+base) % % This software is governed by the CeCILL license under French law and % abiding by the rules of distribution of free software. % See http://www.cecill.info/licences.en.html if strcmp (dataset, 'random') % synthetic dataset d = 16; % Generate a set of unit norm vectors ntrain = 10000; nbase = 1000000; nquery = 1000; vtrain = single (rand (d, ntrain)); vbase = single (rand (d, nbase)); vquery = single (rand (d, nquery)); % Compute the ground-truth t0 = cputime; [ids_gnd, dis_gnd] = yael_nn (vbase, vquery, 1); tgnd = cputime - t0; else switch dataset case 'siftsmall' basedir = './siftsmall/' ; % modify this directory to fit your configuration fbase = [basedir 'siftsmall_base.fvecs']; fquery = [basedir 'siftsmall_query.fvecs']; ftrain = [basedir 'siftsmall_learn.fvecs']; fgroundtruth = [basedir 'siftsmall_groundtruth.ivecs']; case 'sift' basedir = './sift/' ; % modify this directory to fit your configuration fbase = [basedir 'sift_base.fvecs']; fquery = [basedir 'sift_query.fvecs']; ftrain = [basedir 'sift_learn.fvecs']; fgroundtruth = [basedir 'sift_groundtruth.ivecs']; case 'gist' basedir = './gist/' ; % modify this directory to fit your configuration fbase = [basedir 'gist_base.fvecs']; fquery = [basedir 'gist_query.fvecs']; ftrain = [basedir 'gist_learn.fvecs']; fgroundtruth = [basedir 'gist_groundtruth.ivecs']; end % Read the vectors vtrain = fvecs_read (ftrain); vbase = fvecs_read (fbase); vquery = fvecs_read (fquery); ntrain = size (vtrain, 2); nbase = size (vbase, 2); nquery = size (vquery, 2); d = size (vtrain, 1); % Load the groundtruth ids = ivecs_read (fgroundtruth); ids_gnd = ids (1, :) + 1; % matlab indices start at 1 end