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_neg_reg_gen():
# return generate_samples.load_negative_region_generator(classifier_yaml)
# return generate_samples.load_exclusion_region_generator(classifier_yaml)
return generate_samples.load_hard_negative_region_generator(classifier_yaml)
def get_neg_reg_gen():
# return generate_samples.load_negative_region_generator(classifier_yaml)
# return generate_samples.load_exclusion_region_generator(classifier_yaml)
return generate_samples.load_hard_negative_region_generator(
classifier_yaml)
