def __init__(self, config_yaml_fname, pos_frac, exclusion_frac, hard_neg_frac): config_yaml = fileutils.load_yaml_file(config_yaml_fname) self.pos_reg_gen = generate_samples.load_positive_region_generator(config_yaml) self.neg_reg_gen = batch_shuffle(generate_samples.load_negative_region_generator(config_yaml), batch_size=100) self.exc_reg_gen = batch_shuffle(generate_samples.load_exclusion_region_generator(config_yaml), batch_size=5000) self.hard_neg_reg_gen = generate_samples.load_hard_negative_region_generator(config_yaml) self.window_dims = tuple(map(int, config_yaml['training']['svm']['window_dims'])) self.pos_frac = pos_frac self.exc_frac = exclusion_frac self.hard_neg_frac = hard_neg_frac
def __init__(self, config_yaml_fname, pos_frac, exclusion_frac, hard_neg_frac): config_yaml = fileutils.load_yaml_file(config_yaml_fname) self.pos_reg_gen = generate_samples.load_positive_region_generator( config_yaml) self.neg_reg_gen = batch_shuffle( generate_samples.load_negative_region_generator(config_yaml), batch_size=100) self.exc_reg_gen = batch_shuffle( generate_samples.load_exclusion_region_generator(config_yaml), batch_size=5000) self.hard_neg_reg_gen = generate_samples.load_hard_negative_region_generator( config_yaml) self.window_dims = tuple( map(int, config_yaml['training']['svm']['window_dims'])) self.pos_frac = pos_frac self.exc_frac = exclusion_frac self.hard_neg_frac = hard_neg_frac
def get_pos_reg_gen(): return generate_samples.load_positive_region_generator(classifier_yaml)