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dlib
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Refactored the random feature selection function so that it always has bounded 

runtime, even with very bad parameter selections.
This commit is contained in:
Davis King 2018-02-13 07:42:16 -05:00
parent ef4b7a0ef2
commit c38d7e5544
1 changed files with 9 additions and 6 deletions
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15
dlib/image_processing/shape_predictor_trainer.h
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@ -523,15 +523,18 @@ namespace dlib
{
const double lambda = get_lambda();
impl::split_feature feat;
double accept_prob;
do
const size_t max_iters = get_feature_pool_size()*get_feature_pool_size();
for (size_t i = 0; i < max_iters; ++i)
{
feat.idx1 = rnd.get_random_32bit_number()%get_feature_pool_size();
feat.idx2 = rnd.get_random_32bit_number()%get_feature_pool_size();
feat.idx1 = rnd.get_integer(get_feature_pool_size());
feat.idx2 = rnd.get_integer(get_feature_pool_size());
while (feat.idx1 == feat.idx2)
feat.idx2 = rnd.get_integer(get_feature_pool_size());
const double dist = length(pixel_coordinates[feat.idx1]-pixel_coordinates[feat.idx2]);
accept_prob = std::exp(-dist/lambda);
const double accept_prob = std::exp(-dist/lambda);
if (accept_prob > rnd.get_random_double())
break;
}
while(feat.idx1 == feat.idx2 || !(accept_prob > rnd.get_random_double()));
feat.thresh = (rnd.get_random_double()*256 - 128)/2.0;