scalar_t *weak_learner_responses,
scalar_t *current_responses);
- // This method returns in sample_nb_occurences[k] the number of time
- // the example k was sampled, and in sample_responses[k] the
- // consistent response so that the overall loss remains the same. If
- // allow_duplicates is set to 1, all samples will have an identical
- // response (i.e. weight), but some may have more than one
- // occurence. On the contrary, if allow_duplicates is 0, samples
- // will all have only one occurence (or zero) but the responses may
- // vary to account for the multiple sampling.
+ /* This method returns in sample_nb_occurences[k] the number of time
+ the example k was sampled, and in sample_responses[k] the
+ consistent response so that the overall loss remains the same. If
+ allow_duplicates is set to 1, all samples will have an identical
+ response (i.e. weight), but some may have more than one
+ occurence. On the contrary, if allow_duplicates is 0, samples
+ will all have only one occurence (or zero) but the responses may
+ vary to account for the multiple sampling. */
void subsample(int nb, scalar_t *labels, scalar_t *responses,
int nb_to_sample, int *sample_nb_occurences, scalar_t *sample_responses,
// Body location
+ // **********************************************************************
// Useless code, but necessary to keep the exact same results with
// g++ 4.1 and -O3 options on reference experiments.
-
_body_xc = cell->_belly_xc.middle() * discrete_scale_ratio;
_body_yc = cell->_belly_yc.middle() * discrete_scale_ratio;
-
_body_tilt = 0;
-
if((_head_xc - _body_xc) * cos(_body_tilt) + (_head_yc - _body_yc) * sin(_body_tilt) > 0) {
_body_tilt += M_PI;
}
+ // **********************************************************************
// Belly location
// Frames
if(_body_xc >= _head_xc) {
- // if(_belly_xc >= _head_xc) {
+ // if(_belly_xc >= _head_xc) {
_horizontal_polarity = 1;
} else {
_horizontal_polarity = -1;